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Job id: 067949. Salary: £35,502 – £40,333 per annum, including London Weighting Allowance.

Posted: 26 May 2023. Closing date: 31 May 2023.

Business unit: Faculty of Life Sciences & Medicine. Department: Biomedical Engineering.

Contact details: Emma C. Robinson.

Location: St Thomas’ Hospital. Category: Research.

Job description

This is an exciting opportunity for a research assistant trained in cortical modelling to join a collaborative project shared between King’s College London, the FMRIB centre, University of Oxford, and the Donders Institute, Nijmegen

The post-holder will be responsible for building new models of cortical organisation and using them to better understand their links to brain phenotypes and genotypes.  

The successful candidate will have an undergraduate degree in medicine or neuroscience. They will be able to demonstrate excellent software development skills in Python and Pytorch. They will have experience working with cortical surface representations of the brain and working with software tools and pipelines from the Human Connectome Project, Developing Human Connectome Project and UK Biobank open datasets. 

This post will be offered on a fixed-term contract for 12 months (in first instance)  

This is a part time post – 20 hours per week

Key responsibilities

•                     Running and developing cortical image processing pipelines  

•                     Using neuroanatomical knowledge to validate and QC findings

•                     Building machine learning and deep learning models in python and pytorch

•                     Implementing Genome Wide Association Studies of the correlations between brain imaging phenotypes and SNPs

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.

Skills, knowledge, and experience 

Essential criteria  

1.       Degree in Medicine or neuroscience 

2.       Proficiency in Python and PyTorch 

3.       Experience with machine and deep learning models 

4.       Expertise in cortical surface modelling 

5.       Experience in running HCP and dHCP pipelines 

6.       Highly developed verbal and written communication skills  

7.       Ability to work effectively within a collaborative environment with people from a variety of backgrounds 

8.       Comfortable and efficient working independently (at home and in the office) 

9.       Proactive