PhD studentships
PhD studentships are a type of scholarship for your research. Generally, a PhD studentship will provide at least the full standard UK/EU fees, and will usually include a maintenance stipend as well. The studentship will normally focus on an area of research that is of interest to the sponsoring party. Stay tuned for more PhD studentships in the future
Computing PhD studentships
The Faculty of Computing, Engineering and Built Environment (CEBE) is based at our City Centre Campus in Millennium Point. Research is vital to our University: it enables us to contribute new knowledge, underpins our creative and enterprise thinking and ensures we are delivering leading-edge teaching. Our researchers are making significant discoveries and partnering local, national and global organisations to find solutions to contemporary commercial, scientific and social issues. Many of our academic staff engage in research and/or professional practice, and we have a thriving community of postgraduate research students.
The School of Computing and Digital Technology (based within CEBE) currently has PhD Studentships available in a number of specialist areas that present exciting opportunities to join and study with us. Please refer to the details below for further information regarding each available research project.
PhD Classic Doctoral Training Grant Funding Information
This 36 month (3 year) fully-funded PhD Studentship, in-line with the Research Council values, comprises a tax-free stipend of £15,609 per annum (paid monthly). The bursary is renewable annually for up to 36 months in total, subject to you making satisfactory progression within your PhD research.
This funding model also includes a FT Home fees studentship (£4,500 for 2021-22) for up to 3 years, subject to you making satisfactory progression within your PhD research.
This opportunity is open to UK, EU and International applicants. All applicants will receive the same stipend irrespective of fee status, however international applicants will be required to meet the difference in fee costs from their own funds.
Information for International Applicants
International applicants must submit a valid English language qualification, such as International English Language Test System (Academic IELTS) or equivalent with an overall score of 6.5 with no band below 6.0. Further details can be found here: https://www.bcu.ac.uk/international/your-application/english-language-and-english-tests/accepted-qualifications
Deadline for Applications
Formal applications should be made on the University's online application form, which can be found under the 'How to Apply' tab of the PhD course page. The form should be accompanied by an initial research proposal of 1,000-2,500 words (fully referenced) explaining your ideas about the topic and how it might be studied - this allows us to match your ideas with staff experience and interests.
To discuss the application process please contact DRC.CEBE@bcu.ac.uk.
Please ensure you include the Project Code on your proposal. To allow due consideration of applications please also ensure you submit your application by 23:59 on 16th April 2021 for a September start. See below for details of active studentships.
Projects
Elderly Care in Smart Home Environment
Project code: CEBE-PhD-1
Contact for Application Enquires: Dr Peggy Zhu
Email: peggy.zhu@bcu.ac.uk
With the rapid expansion of the ageing population, home-based care is an increasingly important choice for the elderly population in the world. Due to problems associated with ageing, most elderly cannot control their home environment easily without the need of assistance which leads to a growing demand for home care. Home care fees have risen fast in recent years. With the progress of science and technology, various kinds of IoT devices such as smart lighting, heating and various home appliances can be used in smart home environments. Smart homes can help the elderly to improve the comfort of their living environment and manage their life. It can also reduce their dependency on a carer therefore reducing the cost of care.
In a smart home environment, carers can remotely control the home environment to automate various tasks such as generating weekly necessities, purchase lists and getting orders delivered, starting plant water systems, implementing house maintenance systems and anti-drop function etc. This project will investigate and adopt new technologies for smart home environments to support elderly people who are living alone. It will also investigate wearable sensor technologies for remote health monitoring. Data such as electrocardiograms (ECGs), heart rate (HR), blood pressure (BP) and body temperature will be collected and forwarded to the cloud for storage through 4/5G mobile networks.
These data will then be analysed remotely on the cloud for anomaly detection. If an anomaly is detected, the relevant carer will be informed to take appropriate actions. In this project, you will develop wearable sensing and machine learning algorithms for remote health monitoring, and a secure smart home system for assisted living.
Person specification:
- Applicant must have obtained a 2:1 University Degree in Computer Science (or in closely related subject areas) or an equivalent University Degree.
- Applicant must evidence a high working knowledge of English (IELTS Level 7 or higher)
- Applicant must have good programming skills, good knowledge of IoT or wireless sensor networks.
- Familiarity with one or more of the following topics would be an advantage: cloud computing, machine learning and network security.
- Having experience in publishing research findings in conference proceedings is an advantage.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Cooperative AI and Low-Latency Services for Future Autonomous Systems
Project code: CEBE-PhD-2
Contact for Application Enquires: Dr Taufiq Asyhari
Email: taufiq.asyhari@bcu.ac.uk
Autonomous systems are becoming reality and the next coming years will see an ever-increasing provision of their services to support the realisation of a smart and sustainable city. Exemplified into aerial and ground platforms (i.e., drones and robots), these systems serve as automated multi-agents, and can collaboratively play a major role in managing the city’s infrastructure and services, ranging from environmental monitoring and management to healthcare and transportation, including those with time-sensitive requirement. To achieve this potential, it is imperative to equip these automated agents with embedded AI that can flexibly cooperate with each other and rapidly adapt to the uncertainty and changing conditions, particularly for time-critical services.
Birmingham City University is inviting applications for a fully funded PhD studentship in AI and Communication Networks for Autonomous Systems. The project will focus on the interactions between cooperative AI and low-latency services to enhance the capability of future autonomous systems in adapting to uncertainty and changing environment. More specifically, the project will develop methods to model duality of cooperative AI and low-latency, and propose context-aware learning techniques to harness this interdependence. The methods and techniques will then be applied to selected use cases and scenarios in smart city environmental management or transportation. A range of testing and validation strategies will be conducted via a series of simulations and experiments based on the scenarios of interests.
This PhD project will sit within the Future Information Networks (FINET) Research Cluster as part of the Cyber Physical Systems (CPS) Research Group. The Cluster thrives to shape the development of next generation information networks and innovate future network-enabled digital transformations (5G and beyond) that bring transnational and multidimensional impact to our global community. While the project will address the challenges of autonomous systems in smart cities, there will be opportunity to work collaboratively with other domains, for example rural and energy applications.
Person specification:
We are looking for a candidate across a broad range of Computer Science and Electrical Engineering areas who can prove that they can undertake independent research into this new and exciting field. The candidate should fulfil the PhD Entry requirement by BCU. In addition to that, ideally the candidate will have some previous experience in one or more areas of AI, machine learning, data analytics, and/or Communications. Experience of working with automation or autonomous systems (i.e., drones or robots) will be a plus. Demonstrated previous works through published research articles will be an added advantage.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Secure and Trustworthy AI for Cyber-Physical Systems
Project code: CEBE-PhD-3
Contact for Application Enquires: Dr Junaid Arshad
Email: junaid.arshad@bcu.ac.uk
Artificial intelligence and machine learning have witnessed significant rise in recent years with substantial advancements and widespread applications. Computers are able to understand, comprehend text and images better than humans especially with respect to speed and accuracy. Further, the use AI and machine learning is rapidly expanding to safety/mission critical systems where failure or compromise of such algorithms can cause loss of lives. Therefore, the correct/desired behaviour of such systems is of huge significance, putting the resilience of such systems against adversarial attempts to spotlight.
In recent years, an emerging body of work has shown that deep learning models can be vulnerable to adversarial attempts. For instance, in the image classification domain, these attacks are made by adding slight perturbations to the input image, similarly manipulating small number of edges which can adversely affect the performance of graph convolutional neural networks. Due to increasing reliance on intelligent machine learning/artificial intelligence techniques, the implications of successful malicious attempts can be wide-ranging from false negatives to malfunction of critical systems.
This project aims to investigate typical threats to advanced machine learning methods and develop mitigation strategies effective against such threats.
Person specification:
We invite applications from candidates with undergraduate (1st class) or master's qualifications from students with a computer science or related background including engineering or sciences with an inclination for exploring boundaries of existing methods. Knowledge and experience of working with machine learning / artificial intelligence methods will be beneficial.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Haptic Interaction Design: Accessibility in Music-Making Tools
Project code: CEBE-PhD-4
Contact for Application Enquires: Dr Tychonas Michailidis
Email: tychonas.michailidis@bcu.ac.uk
Visual impairment (blind or partially sighted) affects thousands in the UK and millions worldwide. Accessibility to digital information and tools is necessary for engagement and participation within the society, for their educational aspirations and career. Whilst there is a massive effort from charities and organisations to support them, there is a lack of appropriate tools when it comes to computer-based musical creativity (e.g. composition and computer-based performance). Often users are required to adapt to commercially available software to meet their needs. However, such software products are designed for fully able people and not suitable for people with disabilities.
This project proposes to design a set of novel accessibility tools based on haptics to facilitate the communication between visual impaired users and creative software platforms for music creation. The project will rethink the current production tools and propose new ways for processing and experiencing information through haptics. It will challenge current human-computer-interaction paradigms and machine learning techniques with the aim to devise new ways, in which visually impaired users can process information, navigate, interact and collaborate with other blind and non-blind users during the music creation and performing processes.
Haptic solutions have become more and more integrated into academic research and industrial applications to improve user experience. This includes industries like automotive, wearables, gaming and mobile phones. However, the development process of all software in general and creative music software in particular lacks interaction design conventions when it comes to adopting haptics tools. To address this issue, the project will employ machine learning to predict user behaviours, adapt to their interaction styles in real-time and thus provide the best possible haptic experience.
This project will contribute to:
1. Understanding interaction design approaches for HCI accessibility with haptics for blind users;
2. Developing novel machine learning-based algorithms for real-time user interaction with the screen and audio;
3. Enabling haptic-based accessibility for navigation, screen interaction and collaboration.
The successful applicant will be part of the Digital Media Technology Lab (DMT Lab), and work closely with the Data Analytics and Artificial Intelligence Research Group (DAAI), at the Faculty of Computing, Engineering and Built Environment (CEBE) based at our City Centre Campus in Millennium Point.
Person specification:
The successful applicant will have freedom to steer the research towards their interests and strengths:
- A BSc or MSc in relevant field such as Music Technology, Computer Science, Data Analysis and Human Computer Interaction.
- Programming skills
- Good communication skills; especially in written English
- Strong work ethic and the ability to think creatively and independently
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Computational Analysis of Style in Traditional Fiddle Playing
Project code: CEBE-PhD-5
Contact for Application Enquires: Dr Islah Ali-MacLachlan
Email: islah.ali-maclachlan@bcu.ac.uk
The project aims to present a machine learning approach for the classification of fiddle (folk violin) playing styles. This would include development of an accurate note onset detector and feature extraction techniques allowing the analysis of differences in timbre and other aspects of playing style. The project will mainly focus on studying the performance of deep learning networks and evaluate their effectiveness in addressing the research problem.
The research project would consist of the following phases:
- Identifying the key differences in playing style and how to automatically classify them.
- Curating a collection of recordings and developing a ground truth dataset.
- Developing algorithms for classification of stylistic differences, including temporal and timbral analysis.
- Recording of a dataset based on more detailed understanding of stylistic differences.
- Further development of algorithms and techniques to classify stylistic differences between players.
The folk music of the British Isles has great international impact because the music is played in many countries. Studies of this type, using computational analysis alongside ethnographic and musicological studies, are important in identifying key trends in cultural history.
The Computational Ethnomusicology and Machine Learning research groups at BCU have a history of producing high quality papers on MIR (Music Information Retrieval) and other machine learning subjects in international publications. The PhD studentship forms an important part of growth and potential output in this area.
Person specification:
Essential:
- MSc or suitable evidenced experience in an area with scientific or computer analysis content.
- Experienced Matlab or Python user.
- Good understanding of music and music technology.
- Understanding of field and studio recording techniques.
Desirable:
- Good honours degree in a music technology or computer engineering subject area.
- Understanding of machine learning including deep learning.
- Knowledge of musical acoustics and analysis techniques.
- Grounding in musicology/ethnomusicology.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Wellbeing-Integrated Development Environments (WIDEs)
Project code: CEBE-PhD-6
Contact for Application Enquires: Dr Sara Hassan
Email: sara.hassan@bcu.ac.uk
Applications are invited for a PhD student to undertake the WIDEs project. The aim of the project is to contribute a framework for designing Integrated development environments (IDEs) in a mental-wellbeing-aware manner. This framework would comprise models and guidelines for tailoring the design of an existing or new IDE to display options and communicate errors in a mental-wellbeing-aware manner. This framework would be flexible enough to cater for multiple underlying software development processes (e.g. agile development, extreme programming…etc).
The WIDEs framework will be used by software engineers so that they design more mental-wellbeing aware IDEs for Science, Technology, Engineering and Mathematics (STEM) Higher Education (HE) students to use in their programming. Therefore, the main beneficiary of the WIDEs framework is HE STEM students while the main user of the framework is software engineers who design IDEs.
WIDE is motivated by the increasing number of students in higher education with problems related to mental health and lack of wellbeing, especially amongst students in the STEM fields. This is only magnified under current COVID-19 conditions with the abrupt shift to online learning.
We are aiming to create a framework for IDEs to be designed in a mental-wellbeing-aware manner to cater for the mental well-being of STEM HE students in general and computing students in particular. While WIDEs has its seed during COVID times, its benefits will transcend online learning contexts.
Person specification:
To work on this project, it is critical that the application has the following background:
- Strong software engineering skills including knowledge of software design guidelines, patterns and best practices
- An undergraduate degree in a computer science field with a minimum outcome of 2.1.
- Strong programming experience in Java, C#, and/or Python
Additionally, it is desirable that the applicant has the following skills/experience:
- Hands-on experience in health-related software solutions
- Hands-on experience in data analytics
- Expertise in artificial intelligence (AI) concepts and algorithms
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Engineering and Built Environment studentships
The Faculty of Computing, Engineering and Built Environment (CEBE) is based at our City Centre Campus in Millennium Point. Research is vital to our University: it enables us to contribute new knowledge, underpins our creative and enterprise thinking and ensures we are delivering leading-edge teaching. Our researchers are making significant discoveries and partnering local, national and global organisations to find solutions to contemporary commercial, scientific and social issues. Many of our academic staff engage in research and/or professional practice, and we have a thriving community of postgraduate research students.
Engineering
Our engineering staff work collaboratively with business, industrial and academic partners to develop ‘real world’ applied solutions across a range of themes. Currently we are engaged on research projects developing a new generation of robust sensors, inclusive autonomous transport systems, autonomous robotics and drones, and sensor networks (IOT). Staff are also actively engaged in the development of advanced manufacturing systems to deliver lightweight vehicles, cost effective metal forming processes and sustainable systems. A key aspect of this work is its connection to industry and business which is also addressed by our logistics and supply chain team.
Our specialist areas include:
- Nano-fluids and heat transfer
- Earthquake engineering
- Sensors and remote health monitoring
- Fluid and structure mechanics
- Multiphysics fluid structure interaction (FSI)
- Numerical modelling such as Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA)
- Non-linear control of fluid flow
- Knowledge-based engineering
- Wind engineering
- Microfluidics
- Nano-medicine
- Urban drainage systems
- Hydrological performance
- Fibre reinforced composites
- Polymer science
- Product life cycle assessment
- Materials and Manufacturing
Built Environment
Our work focuses on human intervention in the physical environment, with the aim of improving current and future conditions. We are particularly interested in work that explores the problematic gaps between professions, between planning strategy and policy and between the academic and professional worlds.
Our specialist areas include:
- Community engagement and enablement
- Knowledge management and expertise in the construction industry
- Local sustainability
- Post-catastrophe urban reconstruction
- Rural-urban fringe economy and management
- Stakeholders and community engagement
- Urban conservation
We also explore issues including the adoption of digital technologies such as Building Information Modelling (BIM), internet of things, machine learning, and virtual reality, the applications of innovative planning, design and construction approaches such as lean manufacturing and integrated project delivery, and the interfaces amongst human, building and the living environment to future-proof our living environment.
- Data integration and analytics in building life-cycle
- Application of immersive technology in building life-cycle
- Off-site production process design and engineering
- Use of renewable and recyclable structural materials
PhD Classic Doctoral Training Grant Funding Information
This 36 month (3 year) fully-funded PhD Studentship, in-line with the Research Council values, comprises a tax-free stipend of £15,285 per annum (paid monthly). The bursary is renewable annually for up to 36 months in total, subject to you making satisfactory progression within your PhD research.
This funding model also includes a FT Home fees studentship (£4,407 for 2020-21) for up to 3 years, subject to you making satisfactory progression within your PhD research.
This opportunity is open to UK, EU and International applicants. All applicants will receive the same stipend irrespective of fee status, however international applicants will be required to meet the difference in fee costs from their own funds.
How to Apply
Formal applications should be made on the University's online application form, which can be found under the 'How to Apply' tab of the Engineering PhD course page. The form should be accompanied by an initial research proposal of 1,000-2,500 words (fully referenced) explaining your ideas about topic and how it might be studied - this allows us to match your ideas with staff experience and interests.
To discuss the application process please contact DRC.CEBE@bcu.ac.uk.
If you applying for one of the below studentships please ensure you include the Project Code on your proposal. See below for details of active studentships.
Embedding Block Chain Technology within a Facilities Management Common Data Environment
Project code: EBE-122020-PhD-4
Location: BCU, City Centre Campus (Millennium Point), Birmingham.
Bursary: Approx. up to £15,285 per annum.
REF code: EBE-122020-PhD-4 – All candidates to state that “Embedding Block Chain Technology within a Facilities Management Common Data Environment.”
URL link to application: https://www.bcu.ac.uk/courses/bsbe-research-degrees-phd-2020-21
Closing date: 31 March 2021
Commencement date: September 2021
Contact for Application Enquires: Dr Reaz Hasan
For further details on this opportunity please contact:
Telephone: +44 (0)7535 178339 (Dr Chris J. Roberts, Birmingham City University and interview Chair)
E-mail: chris.roberts@bcu.ac.uk; and chri51988@live.com
Telephone: +44 (0)7722 521846 (Professor David J. Edwards, Birmingham City University)
E-mail: david.edwards@bcu.ac.uk; and drdavidedwards@aol.com
Telephone: (Associate Professor Mark Shelbourn, Head of School, Birmingham City University)
E-mail: Mark.Shelbourn@bcu.ac.uk
The advent of Industry 4.0 advanced technologies and the innate ability of these technologies (e.g. building information modelling (BIM), sensor-based networks, internet of things (IoT) etc.) to coalesce as a singular entity has brought about significant opportunities for industry practitioners to gain a competitive edge over national and international competitors.
It is also apparent that a thriving ‘knowledge organization’ as a community of practice is inextricably linked to the continuous flows of data and information embedded within corporate intellectual property (IP). This IP is typically housed on a common data environment (CDE) for building environment facilities and assets. This IP is constantly under threat from nefarious organisations and/or individuals engaged in deliberate acts of cybercrime, espionage or deliberate vandalism. Various initiatives have been undertaken to create a more secure CDE but these tend to focus more upon producing ‘universal and off-the-shelf’ information technology solutions vis-à-vis built upon a real world understanding of facilities and asset management within the built environment.
Project Summary
This study aims to develop a suitable solution to black hatters (nefarious hackers) by working with facilities managers, practitioners and leading academics in the field to develop a novel proof of concept for adopting block chain technologies to protect rich data and information generated through the entire building life-cycle. This will include: rich geometric and semantic ‘as-designed’ BIM models generated prior to construction [lead by Professors David J. Edwards and Mark Shelbourn]; ‘as-built’ BIM models supplied to facility managers (as part of soft landings) [lead by the team]; ‘post-occupancy evaluations (POE) [lead by Dr Chris Roberts]; and other ‘building in-use’ information provided from members of the supply chain, accessed and used by facilities management (for example, building management systems (BMS)). Rather than a ‘top-down’ approach which attempts to force an IT system as a ‘one-size-fit-all’ approach for all users of a CDE, this work will provide a ‘bottom-up’ bespoke and tailored solution to the specific needs and requirements of Facility and Asset management practitioners – this because it will be developed by those experts to understand industry needs best.
Scope of the research
The research seeks to investigate essential core information system data flows, processes and actors that constitute an advanced digital facilities management solution within a CDE. Block chain technological solutions to be adopted to preserve IP rights inextricably linked throughout the supply chain management of a built environment asset throughout its whole life-cycle – from inception through to demolition.
Specifically, the research is broken down into 3 core phases and will: 1). define and delineate processes and procedures for collecting data, information and documents used to manage facilities and assets within the built environment using information systems approaches; 2). identify other sources of data and information that can best optimize facilities management throughout supply chain stakeholders (such as contractors or maintenance engineers) of a building’s whole life cycle; and 3). Building upon points 1 and 2, create a novel and innovative proof of concept for layering and embedding block chain technologies within facilities/asset management. Such work will also engender wider polemic debate as well as signpost future direction for follow on research in this important and specific area of facilities management, and the wider area of built environment science.
The research team members have established a strong international profile in this area of research and have established world-wide linkages with high-profile collaborators who support this studentship. Planning now and preparing applied ‘products’ for industry consumption will enable the realisation of these objectives and this PhD could be instrumental in providing a basis upon which to further expand knowledge and reputation in this novel area of built environment science.
This research reflects contemporary practice at the cutting edge of developments and will prove useful to wider university teaching provisions at all levels of education. For example, the research findings could be successfully integrated into taught courses on the Building Surveyor, Architectural Technology and Construction Management programmes at an undergraduate level but also masters dissertations (for example, ENG7200).
The studentship
The PhD studentship is funded (under a partnership arrangement) by the Faculty of Computing, Engineering and the Built Environment, Birmingham City University. The fully funded studentship is for a three year tenure and provides an excellent opportunity for a self-motivated researcher to work with leading academics and practitioners within the multidisciplinary areas of cyber security within an increasingly digital built environment. Anticipated topics of investigation will include for example: facilities management, building management systems, building information modelling, cyber security and block chain.
The successful candidate will be based in Birmingham, Britain’s second largest city. They will primarily work at Birmingham City University, Millennium Point.
The research required will provide exciting opportunities for a successful candidate who should bring passion to this subject area in order to develop high quality evidence-led research in the important area of block chain integration in contemporary facilities management. Subject to success, this research offers the opportunity to gain a PhD in an important, yet highly novel, area with transferrable skills that will enhance the candidates’ employability prospects.
Applications for the studentship
Birmingham City University (BCU) is committed to equality, diversity and inclusion. The opportunity to study for this fully funded PhD at BCU is an open competition; applications are invited from students from all backgrounds and each fully completed application will be assessed solely on merit during the initial review, to ensure equality of opportunity and freedom from discrimination.
We welcome applications from candidates who can provide evidence of the following essential and desirable attributes and requirements:
Essential:
Personal attributes
- Interest or involvement in digital technologies; block chain; and facilities management in the built environment;
- Good self-management and planning skills that make optimum use of time;
- Accountability for own work, learning from mistakes and the work of others;
- Ability to maintain focus on defined goals and persevere, even in the event of failure;
- Enthusiasm for applied scientific research, with considerable self-motivation;
- Attention to detail, taking time, pride and care to deliver scientifically credible research;
- Trustworthy with the ability to engage individuals and industry, and to build trust in others through open and honest dialogue;
- Respect for others, especially those with conflicting or contradictory views or opinions;
- Willingness to listen to alternative arguments and understand opposing hypotheses;
- Ability to work effectively in an interdisciplinary and geographically distributed team; and
- Good communication skills, enabling ideas to be shared via oral, graphical and written channels.
Core academic requirements
- Sufficient academic acumen to support preparation of written materials such as research publications in academic journals and working journal papers (i.e. to submit at least one Q1 journal paper per annum);
- Understanding of qualitative and quantitative analytical techniques and their application to multi-disciplinary research;
- Knowledge of block chain technology and its applications; and
- An appreciation and understanding of statistical and modelling software that can be used to analyse large sets of both quantitative and qualitative data.
Specific academic requirements
- Proven qualification or competence in at least one of the core areas of research and working knowledge of the remaining core area(s) of research. The core areas of research are: first and foremost, block chain technology but also digital technologies; facilities management; building feedback mechanisms; and knowledge management.
Desirable:
Personal attributes
- Possession of a driving licence for Category B vehicles (cars) is beneficial, as many construction sites are not easily accessible via public transport.
Academic requirements
- Practical knowledge of contemporary digital technologies within the built environment and specifically, block chain and facilities management;
- Practical knowledge of operational environments and the cyber security challenges associated with working within them to deliver a secure digital facilities management environment within the internet of things (IoT);
- Knowledge of pertinent ‘underpinning’ digital theories and philosophies;
- Experience of working within or with the facilities management, construction and civil engineering industries (throughout the whole lifecycle of a building or asset).
Package:
The successful candidate will receive an initial bursary of up to £15,285 per annum, which will be subject to an annual review. This is a three year funded studentship including tuition fees which cover the UK rate plus stipend payments (based upon the applicable ESPRC rate at the point of the award) and additional allowances. International applicants are eligible to apply for this studentship but must meet the shortfall on fees between Home/EU and International rate.
Additional resources will be available to support the practical aspects of the research work, for example via pilots or trials on the network, with the potential (subject to benefit case approval) for the successful candidate to request funds for attendance at appropriate national or international conference events.
How to apply:
Applicants should complete an application form here https://www.bcu.ac.uk/courses/bsbe-research-degrees-phd-2020-21
Applicants are invited to explore our webpages to find more information about the course entry requirements (https://www.bcu.ac.uk/courses/bsbe-research-degrees-phd-2020-21) and our Research Community (https://www.bcu.ac.uk/research/our-phds)
Overseas application must submit a valid International English Language Test System (Academic IELTS) or equivalent, with overall score 6.5 with no band below 6.0 or equivalent https://www.bcu.ac.uk/international/your-application/english-language-and-english-tests/accepted-qualifications)
Recruitment process
Applications should be online through BCU’s application portal before 23:59 on 31st January 2021. All fully completed applications will be considered.
Following initial review of all fully completed applications, successful candidates will be invited to interview for the studentship. All unsuccessful applicants will be advised in writing; unfortunately we cannot provide feedback on applications that were unsuccessful at the initial review stage.
Competence-based interviews will take place via video conference during 15th January 2021 – dates and venue to be confirmed. Interviews will be conducted by an interview panel drawn from BCU and Chaired by Dr Chris Roberts. For any candidates with a disability, we will provide reasonable adjustments for the interview to allow full participation in our recruitment interview process.
Candidates will be notified of an interview appointment time via email.
Placemaking: Processes and Practices
Project code:EBE-122020-PhD-1
Application Deadline: Wednesday 31st March 2021 at 23:59.
Start Date: Monday 6 September 2021
Contact for Application Enquires: Dr David Higgins
Email: david.higgins@bcu.ac.uk
Website: https://www.bcu.ac.uk/built-environment/research/property-planning-and-policies
The Property, Planning and Policies Research Group would like to attract prospective PhD Students to the exciting Placemaking agenda. We invite applications in the following areas of research interest identified in our “Placemaking: Processes and Practices” report (1).
- How can we use digital technology to create sustainable places?
- Is prefabricated urban housing the future of new supply?
- How does energy efficiency affect property values and rents?
- Evaluating recent built environment heritage and urban form.
- How can the transition to urban sustainability effectively facilitated in light of rapid climate and environmental change?
- How can communities create and drive sustainable lifestyles locally?
- What role do communities play in designing the cities of the future?
- Can co-working space create long-term building owner returns?
Applicants are invited to submit a preliminary research proposal of up to 2000 words, fully referenced, clearly identifying their area of interest and a specific project within it, why it is important, and how they would research it. Projects linking any of these areas of interest would also be welcome.
(1) See link: https://www.bcu.ac.uk/built-environment/research/property-planning-and-policies/publications/placemaking-report
Person specification:
Successful applicants will have graduated (or be due to graduate) with an undergraduate first class degree and/or MSc distinction in a relevant real estate / planning subject. Applicants must also demonstrate good knowledge within the urban environment of the contemporary features such as connectivity, sustainability, generational change and governance.
Information for International Applicants:
International applicants must submit a valid English language qualification, such as International English Language Test System (Academic IELTS) or equivalent with an overall score of 6.5 with no band below 6.0.
Funding:
The successful candidate will receive an initial bursary of up to £15,285 per annum, which will be subject to an annual review. This is a three year funded studentship including tuition fees which cover the UK rate plus stipend payments (based upon the applicable ESPRC rate at the point of the award) and additional allowances. International applicants are eligible to apply for this studentship but must meet the shortfall on fees between Home/EU and International rate.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
CFD-based Investigation and Design Optimisation of Thermal Challenges and Active Cooling in Electric Batteries
Project code: EBE-122020-PhD-2
Contact for Application Enquires: Dr Zinedine Khatir, Associate Professor
Email: Zinedine.Khatir@bcu.ac.uk
Website: https://www.bcu.ac.uk/engineering/about-us/our-staff/zinedine-khatir
Deadline: 2 May 2021
In the alteration to a decarbonized electric power system, variable renewable energy (VRE) resources such as wind and solar cells play a key role due to their availability, scalability, and affordability. However, the degree to which VRE resources can be effectively installed to decarbonize the electric power system hinges on the future availability and cost and reliability of energy storage technologies (batteries).
Temperature and humidity level greatly affect the performance, safety, and lifespan of battery cells, thus making their control a key test for battery addition into vehicles. The operating temperature of Li-ion batteries used in modern electric vehicles should be kept within a permissible range to evade thermal runaway and degradation.
Hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are promising technologies to aid decrease the quantity of fuel expended for transportation. In both HEVs and PHEVs, the battery pack is a vital element to allowing their fuel savings potential. The battery is also one of the most costly components in the vehicle. One of the most important factors impacting both the performance and life of a battery is temperature. In particular, operating a battery at elevated temperatures reduces its life.
The effects of heat and thermal management of structures is more and more critical as performance limits are tested further by the need to have lighter, smaller and more efficient designs. Convection, conduction and radiation loads are obvious, but the need to include effect of power losses thermal energy from friction of particles and external sources such as fluid flow within battery means that analyst need to have more tools at their disposal to simulate thermal models accurately.
This PhD project will entail the use of Computational Fluid Dynamics combine with design optimization techniques to investigate thermal management of batteries. The thermal performance of the bus bar as well as microchannel cooling strategies will be analyzed for optimum cooling outcome. The research will focus on reducing cost of battery by reducing thermal losses and improve through active cooling techniques. Experimental work will be undertaken should time and resources permit.
Person specification:
The successful applicant will have, or be expecting, a good Degree and/or Masters (or equivalent) in engineering or physical sciences, with a strong interest in multidisciplinary computational engineering and science, energy and industrial applications and have a strong thermal and fluid dynamics background and knowledge of the use and development of Computational Fluid Dynamics (CFD) tools, specifically OpenFOAM would be an advantage. Experience in CFD-based Design Optimisation techniques and their applications (i.e. Robust and Bayesian Optimisation, Meta-modelling, Surrogate Modelling, Machine/Deep Learning), as well as design of thermal storage and thermal airflow systems are particularly welcome.
Information for International Applicants:
International applicants must submit a valid English language qualification, such as International English Language Test System (Academic IELTS) or equivalent with an overall score of 6.5 with no band below 6.0.
Funding:
Applicants who apply for this project will be considered on a competitive basis in May/June 2021 against candidates shortlisted for this project. Early submission is advised, and a complete application must be received before the advert’s closing date.
The successful candidate will receive an initial bursary of up to £15,285 per annum, which will be subject to an annual review. This is a three year funded studentship including tuition fees which cover the UK rate plus stipend payments (based upon the applicable ESPRC rate at the point of the award) and additional allowances. International applicants are eligible to apply for this studentship but must meet the shortfall on fees between Home/EU and International rate.
How to apply:
To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document.
You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).
Health, Education and Life Sciences studentships
The Faculty of Health, Education and Life Sciences (HELS) is based at our City South Campus. The Faculty has a strong focus on the training of health and education professionals with a rapidly growing life sciences portfolio.
HELS is making major investments in growing the quality and volume of research across its three constituent Schools (The Schools of Education and Social Work, Health Sciences, and Nursing and Midwifery) through investments in academic staff and researchers, doctoral students and new labs and equipment.
This work is led by three centres of research excellence: the Centre for Studies in Practice and Culture in Education (CSPACE); the Centre for Social Care, Health and Related Research (CSCHaRR); and the Centre for Life and Sport Sciences (CLaSS). We are pleased to invite applications for two new fully funded PhD opportunities to support this work.
Funded PhD Opportunities to start Monday 6th September 2021
HELS is seeking to recruit scholars to undertake Graduate Research and Teaching Assistant (GRTA) posts in relation to the following two projects:
- Teaching and Learning in Digital Spaces in Primary ITE (REF: GRTAEDU – apply here)
- How can knowledge mobilisation theory be used to improve radiography education?(REF: GRTAHS – apply here)
GRTA Funding Information
GRTA opportunities at Birmingham City University provide you with an opportunity to study for a PhD whilst gaining experience as an Assistant Lecturer on a funded, 48 month (four-year) programme. The GRTA payments consist of two elements:
- 0.75 GRTA DTG - tax-free stipend paid monthly and has a current (2020/21) value* of £11,463.75 per annum (paid monthly). The bursary is renewable annually for up to 48 months in total, subject to you making satisfactory progression within your PhD research.
- 0.25 fixed term contract of employment (Assistant Lecturer) - renewable for up to 48 months in total, subject to satisfactory performance and progression within your PhD research. Please note that the pro rata salary* for 2020-21 will be £7,707.75 (and this may be subject to some taxation).
This funding model also includes a FT Home fees* studentship (£4,407 for 2020-21) for up to 4 years, subject to you making satisfactory progression within your PhD research.
If you are interested in a career in academia, working as a GRTA enables you to develop a range of transferable skills while building up vital work experience in your field.
GRTA opportunities are open to UK, EU and Overseas applicants. All applicants will receive the same stipend irrespective of fee status, however international applicants will be required to meet the difference in fee costs from their own funds.
We particularly welcome applicants from groups currently under-represented in our research community including LGBT+ applicants, applicants from Black Asian and minority ethnic communities and disabled applicants.
Birmingham City University is Stonewall Diversity Champion and holds an Athena Swan Bronze award. The School of Nursing and Midwifery has recently been awarded a department level Athena Swan Bronze award. At Birmingham City University we are proud to be an equal opportunities employer. All staff are expected to understand and enact the University’s commitment to ensuring equality, diversity and inclusion in our employment practice and in all that we do.
This commitment is enshrined in our Core Values and is detailed in our Equality, Diversity and Inclusion in Employment Policy. The University values and celebrates the diversity of our staff and students; we welcome people from the many different backgrounds and life experiences that reflect the students and the citizens we serve. We do not discriminate against applicants and actively encourage unique contributions and difference in respect of age, ability, disability, sex, gender or gender identity, ethnicity, religion or belief, sexual orientation or transgender status.
* - The funding levels for 2021-22 are likely to increase slightly on the amounts cited for 2020-21.
How to Apply
The closing date for applications is 23.59 on Sunday 25th April 2021.
To apply, please complete the project proposal form and then complete your online application (via the link attached to each individual project) where you will be required to upload your proposal in place of a personal statement. Please ensure you state the relevant project reference on your proposal form.
To support applicants who may wish to find out more about us and the process of applying for a doctoral role we are offering a virtual applicant event on Monday 15th March, 16.00 – 17.00. The format will be a Q and A session with HELS Faculty colleagues and postgraduate researchers (PGRs) focusing on these posts and the HELS environment. Contact drc-hels@bcu.ac.uk to book a place.
Alternatively, you may wish to speak to one of our Directors of Doctoral Research: Dr Kate Thomson, (Kate.Thomson@bcu.ac.uk) Nursing, Midwifery and Allied Health; Dr Tony Armstrong (Tony.Armstrong@bcu.ac.uk) Education.
Projects
1) Teaching and Learning in Digital Spaces in Primary ITE
(REF: GRTAEDU – apply here)
Contacts for informal enquiries: Dr Louise Wheatcroft (Louise.Wheatcroft@bcu.ac.uk)
The Covid 19 crisis has represented significant challenges for the whole education sector, not least with regard to how to provide high quality education at a distance. Teacher education departments have not been immune to this and have had to respond in imaginative and judicious ways. Coupled with this there is increasing recognition that traditional pedagogies, premised on modes of teaching that place the lecturer front and centre, fare poorly online and that a recalibration of lecturer and student engagement and relationships is urgently needed (Guardian, 2020). Consequently, with these challenges also come opportunities to reimagine students’ lived experience in Higher Education. New ways of developing pedagogical and curricular approaches can now be examined that retain the best features of the pre-pandemic Higher Educational experience whilst exploring the potential of still emerging technologies and communication practices. This comes at a time when all ITE providers are considering their response to the new ITT Core Content Framework from September 2020 reflecting a strategic shift from trainee outcomes to a focus on trainee teachers’ education.
This is therefore an exciting opportunity to conduct a full-time PhD study to explore what teaching and learning in digital spaces could look like in Primary initial teacher education. Furthermore, it will also feed into a Faculty wide commitment to developing leading edge pedagogies and our interest in building on the work undertaken in response to the Covid-19 issue.
We welcome proposals that explore ways to grasp the current moment of potential and possibilities and imagine alternative futures; and/or focus on the value of emerging technologies, literacies and communication practices, and that seek to inform policy and practice in this area with a view to addressing issues of teacher recruitment and retention. It is anticipated that the focus will be on Primary Initial Teacher Education and the higher education space, and /or home/school literacies and engagement.
The specific area to explore will depend upon the candidate and their field of expertise and interests.
In addition to a background in primary education, a postgraduate qualification, or equivalent practice experience, the successful candidate will have an enthusiasm for teacher education and a commitment to contributing to high quality undergraduate teaching on programmes relevant to their specialism.
References
Guardian (2020) Lecturer and Student relationships matter even more online than on campus. (online) Available at https://www.theguardian.com/education/2020/jun/08/lecturer-and-student-relationships-matter-even-more-online-than-on-campus#maincontent (Accessed 09 June. 2020)
DfE (2019) ITT Core Content Framework. (online) Available at https://www.gov.uk/government/publications/initial-teacher-training-itt-core-content-framework (Accessed 09 June 2020)
2) Project Title: How can knowledge mobilisation theory be used to improve radiography education?
(REF: GRTAHS – apply here)
Contacts for informal enquiries: Dr K Louise McKnight (Louise.Mcknight@bcu.ac.uk), Professor Fiona Cowdell (Fiona.Cowdell@bcu.ac.uk), Dr Thomas Hopkins (Thomas.Hopkins@bcu.ac.uk)
Effective education is essential to preparing the next generation of independent practitioners. Our radiography students spend approximately half their time in the university academic setting, and half in the practicum, working and learning alongside staff in clinical imaging departments. Therefore, clinical staff are key to educating students and importantly there needs to be shared knowledge and understanding across student-clinical staff- academic boundaries. Knowledge mobilisation, put simply ‘moving to where it is most useful’ is an emerging field of study in health care and education.
The successful candidate will employ qualitative research methods to explore how knowledge is currently mobilised across student-clinical staff- academic boundaries to support best practice in student education. The study will be informed by the four pillars of advanced practice namely research, clinical skills, education and leadership, and the Society of Radiographers Practice Educator Accreditation Scheme (PEAS).
This GRTA post offers an HCPC registered Diagnostic Radiographer a unique opportunity to both teach students in the university setting and undertake doctoral study investigating how knowledge mobilisation theory may be used to improve radiography education, ultimately for the benefit of patients. The Department of Radiography at BCU educates students on undergraduate courses in Diagnostic Radiography, Therapeutic Radiography and Medical Ultrasound. The successful GRTA will contribute teaching in one or more of these areas.