Postdoctoral Research Associate in deep learning for neuroimage analysis

King's College London; London; On-site; GBP 45,000 - 60,000; Full time

Job summary

A prominent academic institution in London is seeking an expert in medical image deep learning to develop efficient segmentation algorithms. The role requires a PhD and experience with deep learning models, especially in neuroimaging. The successful candidate will collaborate within a multidisciplinary team, contribute to high-quality research publications, and assist in clinical applications. This is a full-time position with a fixed-term contract until July 31, 2028.

Qualifications

• Experience developing deep learning segmentation models.
• Familiarity with medical images such as MRI, CT, or volumetric ultrasound.
• Strong written and oral communication skills, with evidence of publishing peer-reviewed research articles.

Responsibilities

• Develop computationally efficient deep learning models for neuroimaging.
• Validate models on diverse clinical data including MRI and CT.
• Publish developed algorithms in high-quality medical image computing journals.

Skills

Deep learning

Medical imaging computing

Computationally efficient deep learning

Generalisation techniques

Model translation to clinic

Education

PhD in relevant subject area

Tools

Pytorch

MONAI

CUDA

Job description

About Us

We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms.

We welcome application from individual with experience in:

• Deep learning
• Medical imaging computing (preferably neuroimaging)
• Computationally efficient deep learning
• Deep learning model generalisation techniques.
• Translating deep learning models to the clinic

The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King's College London, a vibrant community of engineers designing and translating technology into the clinical. This role will be supported by the Quality Management Systems team at London Institute for Health Care Engineering who will collaborate closely with the group to ensure internal and regulatory requirements are met for the developed quality management system.

About The Role

We are looking for someone with a passion for translating deep learning models into the clinical as part of a team. This role is focused on developing computationally efficient deep learning models to perform neuroimaging segmentation tasks to help inform treatment decisions within a busy neurosurgical centre.

In this role the successful candidate will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed tomography (CT). In this role the successful candidate will write and seek to publish the developed state-of-the-art algorithms in high quality medical image computing journals and conferences. The successful candidate will work with a three-person team of software engineers to integrated algorithms into the Epilepsy Navigation (EpiNav) software platform for stereotactic neurosurgery planning. The successful candidate will help to support the team to formally document algorithms within a quality management system.

EpiNav provides state-of-the-art computer-assisted support for the planning of stereotactic neurosurgery procedures. It has been in daily clinical use at the National Hospital for Neurology and Neurosurgery for over 7 years aiding neurologist and neurosurgeons in the surgical treatment of over 150 patients with medically refractory epilepsy and brain tumour biopsy. This software enables clinicians to use complex multi-modal imaging to inform surgical decisions. Based on the early success of EpiNav to help improve patient care we are refining and streamlining the software so that it is suitable for use outside of a research setting. The team is multidisciplinary consisting of experts in medical image computing, medical regulation, neuroimaging and neurosurgery.

This is a full time post (35 Hours per week), and you will be offered a fixed term contract until 31/7/2028

About You

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

Essential criteria

1. PhD qualified in relevant subject area*
2. Experience developing deep learning segmentation models
3. Experience with Pytorch, MONAI, CUDA or equivalent software libraries for developing deep learning models.
4. Familiarity with medical image such as MRI, CT, or volumetric ultrasound.
5. Knowledge on common medical imaging data augmentation techniques for robust model design.
6. Strong written and oral communication skills including evidence of publishing peer reviewed research articles.

Desirable criteria

1. Experience working with neuroimaging
2. Experience deploying deep learning models into clinical settings
3. Experience working within a development team and associated tools (git, svn or equivalent version control)
4. Experience working with multidisciplinary teams including people from non-technical backgrounds
5. Experience with developing or deploying light weight models in environments with restricted resources (e.g. outside of HPC environments)

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.

We are able to offer sponsorship for candidates who do not currently possess the right to work in the UK.