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- Tasks: Develop and run finite element models to study fetal brain growth impacted by COVID-19.
- Company: Join a leading research team at King's College London focused on innovative biomedical engineering.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional development.
- Why this job: Make a real difference in understanding fetal brain development through cutting-edge research.
- Qualifications: PhD in Biomedical Engineering or related field, with FEM and programming experience.
- Other info: Collaborative environment with access to advanced research facilities and support.
The predicted salary is between 39000 - 46000 £ per year.
The Research Department of Biomedical Computing, within the School of Biomedical Engineering & Imaging Sciences, develops computational methods and AI technologies for automated diagnosis, prognosis and streamlining of clinical workflows. In MeTrICS lab we are mostly focused on the methods for analysing and simulating human brain imaging data. At the Centre for Developmental Neurobiology (CDN), we investigate the mechanisms governing the formation of the brain during embryonic development and in early postnatal life. This is based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience. We are still far from a complete understanding of how these processes work. CDN is one of four departments in the School of Neuroscience at the Institute of Psychiatry, Psychology & Neuroscience and is located at Guy’s campus. Researchers have access to support facilities in genotyping, molecular biology and Drosophila work. CDN has close partnership with the Medical Research Council (MRC) and CDN researchers, together with clinical researchers from King’s, make up the MRC Centre for Neurodevelopmental Disorders.
We are seeking a Research Associate (RA) to work on our Brain Health in Gen2020 study, which seeks to understand the mechanisms by which fetal infection – specifically from COVID-19 - impact fetal cortical development and folding. Our specific interest is in finding someone with experience of running finite element models (FEM) of soft tissue mechanics. It is essential that the successful applicant can directly translate mathematical models to code (rather than directly apply FEM software) since the long-term objective is to translate the methods to a learning-based (AI) framework. The first requirement of this RA role will be to run models of fetal cortical folding to use as training data for physics-constrained AI simulations. Over the course of the project the applicant would be expected to translate these solutions into novel AI frameworks that learn from longitudinal imaging data. Data sources include both macrostructural (whole brain) MRI and microstructural (microscopy) of primary tissue slice cultures. This is a full-time post (35 Hours per week), and you will be offered a fixed term contract for 18 months.
To be successful in this role, we are looking for candidates to have the following skills and experience:
- PhD in Biomedical Engineering (or related discipline) – awarded or thesis submitted
- Experience with running Finite Element Models (FEM)
- Ability to translate mathematical models of cortical folding from papers directly into code
- Programming experience in Python and/or C++
- Use of FEM software e.g ANSYS
- Evidence of publishing papers in reputable conference proceedings or journals
- Ability to work effectively as part of a multidisciplinary team
- Skilled in explaining technical methods to a general audience
- Experience with machine learning
- Coding in PyTorch
- Evidence of published work simulating soft tissue mechanics
- Experience supervising junior team members and PhD students
Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.
We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King’s. As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.
Grade and Salary: £45,031 - £52,514 per annum, including London Weighting
Job ID: 128425
Close Date: 28-Oct-2025
Contact Person: Dr Emma C Robinson / Dr Katie Long
Contact Details: Emma.robinson@kcl.ac.uk / Katie.long@kcl.ac.uk
Research Associate in Finite Element Models of Fetal Brain Growth employer: King's College London
Contact Detail:
King's College London Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate in Finite Element Models of Fetal Brain Growth
✨Tip Number 1
Network like a pro! Reach out to people in your field, especially those connected to the Research Department of Biomedical Computing. Attend relevant events or webinars and don’t be shy about introducing yourself. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! If you’ve got experience with finite element models or coding in Python/C++, consider creating a portfolio or GitHub repository showcasing your projects. This can really set you apart when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of fetal brain development and soft tissue mechanics. Be ready to discuss how your background aligns with the goals of the Brain Health in Gen2020 study. Confidence is key!
✨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 genuinely interested in being part of our community at King’s. Good luck!
We think you need these skills to ace Research Associate in Finite Element Models of Fetal Brain Growth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience with finite element models and any relevant programming skills. We want to see how your background aligns with the role, so don’t hold back on showcasing your achievements!
Craft a Compelling Supporting Statement: Your supporting statement is your chance to shine! Use it to explain how you meet the essential criteria listed in the job description. Be specific about your experiences and how they relate to the research we do at StudySmarter.
Showcase Your Publications: If you've published papers or presented at conferences, make sure to mention them! This shows us that you’re engaged in the field and can communicate complex ideas effectively, which is super important for this role.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need about the role and the application process there.
How to prepare for a job interview at King's College London
✨Know Your FEM Inside Out
Make sure you brush up on your finite element models (FEM) knowledge. Be prepared to discuss how you've applied FEM in your previous work, especially in soft tissue mechanics. They’ll want to see that you can translate mathematical models into code, so be ready to explain your process.
✨Showcase Your Coding Skills
Since programming experience in Python and/or C++ is crucial, come armed with examples of your coding projects. If you've worked with PyTorch or any machine learning frameworks, highlight those experiences. Being able to demonstrate your coding prowess will set you apart.
✨Communicate Clearly
You’ll need to explain complex technical methods to a general audience, so practice simplifying your explanations. Think about how you would describe your research to someone without a technical background. Clear communication is key in a multidisciplinary team.
✨Prepare Your Questions
Interviews are a two-way street! Prepare thoughtful questions about the Brain Health in Gen2020 study and the team dynamics. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
