Research Associate in AI for Computer Assisted Screening of Fetal Cortical Abnormalities

King's College London; London; On-site; GBP 35,000 - 45,000; Full time

Job summary

A prestigious research institution in London seeks a Research Associate for a 2-year project focused on developing AI tools to detect brain abnormalities from fetal MRI scans. Candidates should have a PhD in Biomedical Engineering or Computing, programming experience in Python, and knowledge of cortical neuroanatomy. The role involves developing AI algorithms to chart fetal brain development and requires strong teamwork and communication skills.

Qualifications

• PhD in Biomedical Engineering or Computing - awarded or near completion.
• Display excellent knowledge of cortical neuroanatomy.
• Programming experience in Python.
• Experience with machine learning - particularly normative modelling.
• Familiarity with neuroimage processing tools like FSL.

Responsibilities

• Develop and train AI algorithms for fetal cortex modeling.
• Chart normative development of cortical folding across gestation.

Skills

Knowledge of cortical neuroanatomy

Programming experience in Python

Machine learning experience

Familiarity with neuroimage processing tools

Excellent communication skills

Teamwork ability

Education

PhD in Biomedical Engineering or Computing

Tools

FSL

Connectome Workbench

PyTorch

Job description

About Us

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 development of tools for analysing biomedical surfaces and graphs, predominantly for modelling human brain development.

About The Role

We are seeking a Research Associate to work on our MRC funded grant: Computer Assisted Screening of Cortical Abnormalities in Development (CASCADE) - the objective of which is to develop a suite of AI tools for automating the detection of brain abnormalities from fetal MRI.

During neurodevelopment the human brain surface (cortex) folds as a result of biomechanical tensions that arise as cortical tissues expand more rapidly than the white matter tissues below. Errors at any stage can result in cortical malformations, which are in turn implicated in a broad range of neuropsychiatric impairments. Unfortunately, detecting malformations at an early enough stage to meaningfully intervene is difficult, because each human's brain folds in very different ways. This grant seeks better understand this process in order to disentangle natural sources of variability from signs of disease, to ultimately provide clinicians with an easy-to-use toolkit that will allow them to visualise the fetal cortex as a surface, with annotations that point to sites of potential malformation (even before they form).

The RA on this project would be required to develop and train novel AI algorithms for extracting surface models of the fetal cortex and transient tissues from structural MRI scans; then will use these to chart the normative development of cortical folding across gestation.

This is a full-time post (35 Hours per week), and you will be offered a fixed term contract for 2 years.

About You

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

1. PhD in Biomedical Engineering or Computing - awarded or near completion*
2. Display excellent knowledge of cortical neuroanatomy
3. Programming experience in Python
4. Experience with machine learning - particularly normative modelling
5. Familiarity with neuroimage processing tools e.g. connectome workbench and FSL
6. Excellent written and verbal communication skills
7. Ability to work effectively as part of a team

Desirable criteria

1. Experience with deep learning
2. Coding in PyTorch
3. Experience with cortical surface modelling
4. Evidence of publishing papers in top neuroimaging or AI conferences or journals.

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click "Apply Now". This document will provide information of what criteria will be assessed at each stage of the recruitment process.

Further Information

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.

To find out how our managers will review your application, please take a look at our ' How we Recruit ' pages.