|Salary:||£40,386 to £47,414 per annum, including London Weighting Allowance|
|Placed On:||25th November 2022|
|Closes:||3rd January 2023|
We are seeking a post-doctoral research associate to develop novel artificial intelligence algorithms to analyse video data obtained as part of routine clinical video-telemetry of patients with epilepsy. Video-telemetry data comprises simultaneous recording of video and EEG data. Clinically, video-telemetry data is reviewed by trained neurologists to infer brain regions involved in epileptic seizure onset and spread. The post holder will develop artificial intelligence algorithms to characterise patient motion during seizure from the video data and use this information to classify seizures into different, clinically relevant, subtypes. Ultimately this research could aid clinicians in identifying brain regions involved in seizure onset for specific subtypes to assist in determining appropriate treatment.
In this role, the post holder will be responsible for the development of novel artificial intelligence algorithms to assess video data, working closely with Dr. Rachel Sparks, a Lecturer in the Department of Surgical & Interventional Engineering. Candidates should have demonstrable experience in designing or using deep learning algorithms applied to either medical images, natural images, or video data. Candidates are expected to have demonstratable experience with PyTorch, TensorFlow, or an equivalent software package. Familiarity with version control software (git) and experience working within a multi-developer team is desirable.
This project is part of a close collaboration with experts in epilepsy diagnosis and treatment and King’s College Hospital. As such the successful candidate will be able to work closely with experts in epilepsy to understand the clinical context of the problem and obtain feedback on the methods developed.
The successful candidate is expected to disseminate their research through presenting at scientific conferences, such as MICCAI or MIDL, publications in peer-reviewed journals, and providing open-source code to the developed methods. Candidates are expected to have a good track record of scientific publications in computer vision or medical imaging journals or equivalent conference publications. Candidates should have strong written and oral presentation skills.
Candidates will be based in the Department of Surgical and Interventional Engineering (SIE) reporting to Dr. Rachel Sparks, a Lecturer specialising in neurosurgical planning and treatment. SIE has an open, collaborative environment with the potential for close collaborations. The successful candidate will have the ability to collaborate with other researches, attend regular seminars, and potentially apply their algorithm to other related clinical problems.
This post will be offered on a fixed-term contract for 18 months
This is a full-time post
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
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