Research Fellow in MRI applied to epilepsy

About Us

The post will be based at St Thomas' Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King's College London: . There is an unmatched infrastructure within the School to support cutting-edge translational research, including one of the UK's only 7 Tesla MRI systems located inside a hospital environment, state-of-the-art engineering and physics laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering.

About The Role

Severe epilepsy has a devastating impact on the lives of patients and their families. For many patients' medication is ineffective and surgery is the only curative treatment. However, surgery requires confident knowledge of the location of the epilepsy lesion (abnormal tissue whose aberrant electrical activity causes seizures). We are pioneering the use of Ultra-high field 7T MRI and AI based lesion detection to allow more patients to benefit from life-changing surgery.

You will join a project team of post-doctoral scientists, Imaging physicists, Neurologists, Clinical Neurophysiologists and Neuro-Radiologists at KCL and Cambridge Universities and their partner hospitals to achieve this aim.

You will be responsible for optimising data acquisition and processing through novel methodological development in either image acquisition, reconstruction or post-processing (e.g. AI-based lesion identification) under the primary direction of Prof David Carmichael. You will also ensure the delivery of high-quality data to the clinical research team to meet the clinical research objectives.

This is a full time post (100% FTE), and you will be offered fixed term contract until 10th November 2029.

About You

You will be a technically gifted researcher establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research.

Essential criteria

• PhD qualified in relevant subject area
• Ability to work as part of a team to collect research data in patients
• Strong analytical and technical skills (e.g. in MRI physics, AI, image processing or reconstruction)
• Strong computational skills (e.g. coding in python, bash, matlab)
• Demonstrated aptitude for research
• Problem solving ability
• Ability to work in a multidisciplinary team
• Ability to work without close supervision

Desirable criteria

• Expertise in MRI physics and technology
• Experience in working together with physicians or scientists in the field of MR imaging or clinical research
• Experience of pulse sequence programming (particularly IDEA) or image reconstruction
• Experience of computational modelling and simulatxion
• Knowledge of statistical and/or machine learning methods e.g. for 3D imaging data for applications such as segmentation, registration or lesion detection.

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.

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.