Applications are invited for three Engineering and Physical Sciences Research Council funded Doctoral Training Partnership PhD studentships within the School of Science and Technology.
- Qualification Type: PhD
- Title of project: see below for the three projects available
- Closes: 15th July 2022, or until places have been filled.
Overview
Applications are invited for three Engineering and Physical Sciences Research Council (EPSRC) funded Doctoral Training Partnership (DTP) PhD studentships starting 1st October 2022 within the School of Science and Technology at City, University of London.
Funding
Successful applicants will receive an annual stipend (bursary) of £18,000 plus payment of their full-time tuition fees for a period of up to 48 months (4 years).
Eligibility and requirements
Applicants should be eligible for home (UK) tuition fees, however exceptional overseas candidates may be considered as well. Overseas students whose mother tongue is not English must meet any one or a combination of the following:
- A minimum IELTS average score of 6.5; with a minimum of 6.0 in each of the four components
- The award of a Masters’ degree, the teaching of which was in English from an English-Speaking country.
We are particularly keen to encourage applications from groups which are otherwise underrepresented within our disciplines, especially from women and/or those from minority ethnic backgrounds, and individuals from non-traditional career routes.
Additional project-specific academic requirements are also specified below by the relevant project. These will need to be taken into consideration as well, before applying.
Available projects
These DTP PhD studentships are available to support research in the following three projects:
Project 1: Verifying AI systems by extracting automata via learning
Project title
Verifying AI systems by extracting automata via learning
Project aim and introduction
Artificial intelligence is used widely nowadays including for safety-critical systems. Hence, ensuring AI programs behave the way they are expected to, has become of utmost importance.
However, verifying AI systems is a challenge, both from a theoretical and from a practical point of view.
The project aims at investigating how to extract mathematical models (such as automata) from AI systems (such as neural networks) to capture their behaviour.
Research centre
Artificial Intelligence Research Centre (CitAI)
Eligibility and requirements
Applicants for this scholarship, should have an upper second-class honours BSc (or equivalent, or higher) degree in Computer Science Mathematics or related discipline together with relevant experience.
In particular, a strong background in theoretical computer science is desirable.
Please also note the additional eligibility and requirements listed at the top of the page.
How to apply
Initial informal enquiries should be addressed to Laure Daviaud.
Visit our Computer science research degrees web page for further information on making a formal application, as well as the How to apply section below.
Project 2: Bacterial magnetosome inspired material discovery for high sensitivity to ultra-low magnetic fields
Project title
Bacterial magnetosome inspired material discovery for high sensitivity to ultra-low magnetic fields
Project aim and introduction
The project proposes a pioneering, cross-disciplinary and collaborative research to identify and quantify the underpinning science for highly sensitive, naturally evolved magnetosome behaviour in response to the ultra-low Earth Magnetic Field, to translate that behaviour into a micromechanical mechanism that can be synthetically re-produced, utilising computational multi-physics modelling, experimental instrumentation, and micro-testing.
Applicants with essentially strong computational modelling experience, and preferably with multi-physics, MD and DFT modelling are encouraged to apply.
The research will be conducted in collaboration with several industrial and academic partners in UK and EU.
The successful candidate will be expected to travel to visit partners, publish in top rank journals and attend/present in world-leading conferences such as the International Conference on Composite Materials.
Research centre
Aeronautics and Aerospace Research Centre
Eligibility and requirements
Applicants for this scholarship, should have an upper second-class BSc/BEng/MEng (or equivalent, or higher) degree in aeronautics/aerospace or mechanical/material engineering or other relevant fields.
They should demonstrate aptitude for original research.
Please also note the additional eligibility and requirements listed at the top of the page.
How to apply
Initial informal enquiries should be addressed to Hamed Yazdani.
Visit our Mechanical Engineering and Aeronautics research degrees web page for further information on making a formal application, as well as the How to apply section below.
Project 3: Deep learning for reduced order modelling of wall bounded, turbulent flows
Project title
Deep learning for reduced order modelling of wall bounded, turbulent flows
Project aim and introduction
Simulation (and detailed experiments) of turbulent fluid may be defined as a “data-rich, knowledge-poor” activity: the complexity of underlying physics is so high that it is almost impossible to learn and extract new knowledge from a large amount of the observed data directly.
This thesis will focus on data accumulated with high fidelity simulations to build effective reduced order models set up using a feed forward neural network.
Once a reduced order model is available, one can have rapid estimates of flow field changes as the parameters are changed.
This can be used as an environment for reinforcement learning algorithms.
Research centre
Aeronautics and Aerospace Research Centre
Eligibility and requirements
Applicants for this scholarship, should have an upper second-class BSc/BEng/MEng (or equivalent, or higher) degree in aeronautics/aerospace, mechanical engineering, computer science or related disciplines.
They should demonstrate aptitude for original research.
Please also note the additional eligibility and requirements listed at the top of the page.
How to apply
Initial informal enquiries should be addressed to Daniel Chicharro or Alfredo Pinelli.
Visit our Mechanical Engineering and Aeronautics research degrees web page for further information on making a formal application, as well as the How to apply section below.
How to apply
Visit our relevant research degrees web page (as listed above) for further information on making a formal application.
When submitting your application, enter the relevant project title (as listed above) and you will automatically be considered for this studentship.
You do not need to submit a proposal as part of your application as the project has already been outlined.
The online application can be found in the ‘How to apply section’ in the web links above and should include the following supporting documents:
- Copies of Degree Certificates and Transcripts in official English translation - original will be requested before an offer is made.
- Official work e-mail addresses (not private ones) for two referees (one of which must be an academic).
- Proof of English Language proficiency (minimum average score of 6.5 IELTS, with a minimum of 6.0 in each of the four components) if English is not your first language.
- Passport.
The outcome of the selection process should be announced by the end of August. The successful candidate will formally start their doctorate in October 2022.
For queries regarding the application process, please email the School.
Equality, diversity and inclusion
City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture, for our whole community, including staff, students and visitors.
We welcome applications regardless of gender, sexual orientation, disability, marital status, race, nationality, ethnic origin, religion or social class. For more information on our approaches to encouraging an inclusive environment, please see our Equality, Diversity and Inclusion pages.