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- Tasks: Conduct cutting-edge research on non-Newtonian flows using machine learning and computational fluid dynamics.
- Company: Join City St George's, a leading health-focused university in London.
- Benefits: Enjoy a competitive salary, pension scheme, and extensive training opportunities.
- Why this job: Make a real impact in healthcare technology with innovative cooling solutions for electric motors.
- Qualifications: PhD in Mechanical Engineering or Physics, with experience in computational research and machine learning.
- Other info: Be part of a diverse community committed to equality and inclusion.
The predicted salary is between 43482 - 44746 £ per year.
SCHOOL / SERVICE
School of Science & Technology
DEPARTMENT
School of Science & Technology
LOCATION
College Building
CONTRACT TYPE
Fixed-term
JOB CATEGORY
Research
HOURS
Full-time
SALARY MIN
£43,482
SALARY MAX
£44,746
PUBLICATION DATE
15-Oct-2025
CLOSING DATE
09-Nov-2025
City St George\’s, University of London is the University of business, practice and the professions and brings together the expertise and excellence of City, University of London and St George\’s, University of London into one institution.
The combined university is one of the largest suppliers of the health workforce in the capital, as well as one of the largest higher education destinations for London students.
Combining a breadth of disciplines across health, business, law, creativity, communications, science and technology, we are creating a \’health powerhouse\’ for students, researchers, the NHS and partners in uniting a world-leading specialist health university. We are now one of the UK\’s largest health educators, where staff and students have access to an expanded team of brilliant academic and professional services colleagues, combined resources and facilities and more interdisciplinary opportunities.
The merger creates opportunities to generate significant change in the world of healthcare including changes to treatment, population health monitoring, workforce development and leadership, policy, and advocacy.
Background
City, University of London along with Otto von Guericke University Magdeburg, Lund University, National Technical University of Athens and industrial partners Lubrizol Ltd and AVL List Gmbh participate in the project E-COOL, \’A Holistic Approach for Electric Motor Cooling\’ , funded by the European Innovation Council. E-COOL aspires to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The Team is looking to appoint one Postdoctoral Research Associate on Machine-Learning Assisted Simulation of non-Newtonian Flows.
Responsibilities
The Team aims to synthesise novel, non-Newtonian coolants to be employed in spray-cooling systems for e-motor stator windings. In order to achieve this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training datasets for the ML tool, which will be based on a Tensorial Neural Network architecture, will be provided by Molecular Dynamics simulations also conducted in E-COOL.
Person Specification
The successful candidate will have a first-class degree and PhD in Mechanical Engineering, Physics or relevant fields. They will have experience in computational research in the field of the project, with a strong background in rheology and Non-Newtonian flows. In addition, they will be familiar with Machine-Learning tools (such as PyTorch or TensorFlow), as well as with code development and customisation. They should be able to showcase a proven track record of peer-reviewed activity in research
Additional Information
Closing date: 9th November 2025 at 11:59pm.
The selection process will involve an interview and a presentation. Further details will be confirmed at the interview stage. (If the selection process will include a presentation or test, please provide details and be prepared to accommodate any reasonable requests for candidates with a declared disability or who are making an application under the Guaranteed Interview Scheme).
To apply and for more information about the post please use the links below.
City St George\’s offers a sector-leading salary, pension scheme and benefits including a comprehensive package of staff training and development.
City St George\’s, 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 age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background.
City St George\’s operates a guaranteed interview scheme for disabled applicants.
The University of business, practice and the professions.
Postdoctoral Research Associate employer: City St George's, University of London
Contact Detail:
City St George's, University of London Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Postdoctoral Research Associate
✨Tip Number 1
Network like a pro! Reach out to your connections in academia and industry. Let them know you're on the lookout for opportunities, especially in fields related to Machine Learning and non-Newtonian flows. You never know who might have a lead or can put in a good word for you!
✨Tip Number 2
Prepare for that interview! Brush up on your knowledge of rheology and Machine Learning tools like PyTorch or TensorFlow. Be ready to discuss your past research and how it relates to the role. Practising common interview questions can really help you stand out.
✨Tip Number 3
Showcase your work! If you've got any publications or projects that highlight your expertise, make sure to mention them during your interview. Having tangible examples of your research can really impress the hiring team.
✨Tip Number 4
Don't forget to apply through our website! It's the best way to ensure your application gets seen. Plus, it shows you're serious about joining our team at City St George's. Good luck!
We think you need these skills to ace Postdoctoral Research Associate
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the specific role of Postdoctoral Research Associate. Highlight your relevant experience in computational research, rheology, and Machine Learning tools like PyTorch or TensorFlow. We want to see how your background aligns with our project goals!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Be sure to reference the essential criteria from the person specification and show us your passion for the project E-COOL and its objectives.
Showcase Your Research Achievements: Don’t forget to include your track record of peer-reviewed research. We love seeing evidence of your contributions to the field, so make sure to mention any publications or significant projects that demonstrate your expertise in non-Newtonian flows.
Apply Through Our Website: We encourage you to apply through our website for a smooth application process. Make sure to submit your CV and cover letter by the closing date, 28th September 2025, at 11:59pm. We can’t wait to see what you bring to the table!
How to prepare for a job interview at City St George's, University of London
✨Know Your Research
Make sure you’re well-versed in the specifics of your research area, especially non-Newtonian flows and machine learning applications. Be ready to discuss your previous work and how it relates to the E-COOL project.
✨Prepare for Technical Questions
Expect questions that dive deep into your technical expertise, particularly around computational fluid dynamics and rheology. Brush up on relevant algorithms and tools like PyTorch or TensorFlow, as they may ask you to explain your experience with them.
✨Showcase Your Collaboration Skills
Since this role involves working with a diverse team, be prepared to discuss your experience in collaborative projects. Highlight any interdisciplinary work you've done and how you’ve effectively communicated complex ideas to different audiences.
✨Practice Your Presentation
As part of the selection process, you’ll likely need to present your research. Create a clear, engaging presentation that showcases your findings and methodologies. Practise delivering it confidently, as this will demonstrate your communication skills and passion for the subject.
