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Research Fellow in Machine Learning

Faculty of Medicine

Location:  Highfield Campus
Salary:   £30,942 to £38,017 per annum
Full Time Fixed Term (until 28/02/2021)
Closing Date:  Wednesday 12 February 2020
Interview Date:   Monday 24 February 2020
Reference:  1227420AF

Applications are invited for a Postdoctoral Research Fellow position at the University of Southampton funded by the Alan Turing Institute (https://www.turing.ac.uk/).

The aim of the research project is to use modern machine learning methods, particularly tools from transfer learning, to map complex biology between species. Transfer learning is the branch of machine learning that takes information learnt from one setting and uses it to improve generalisation in another setting. The central idea of transfer learning is to mimic the human ability to learn new concepts from very few examples by associating new information with prior understanding. In this project we will use transfer learning to investigate how the biology of widely-used model organisms (such as the mouse) maps to human biology, and in particular to determine: (1) when biology learnt from a model organisms will map effectively to the human and when it will not; (2) if accurate models of human biology can be learnt from sparse human datasets by leveraging of prior knowledge, in the form of machine learning models pre-trained on data obtained from model organisms. We will start by developing methods to interpret single cell profiling of mouse and human bone marrow samples, which have already been generated in the MacArthur lab, as a representative example. It is anticipated that other sources of data (including histology images) and tissues will be explored as the project develops.

The successful candidate will be based at the School of Mathematical Sciences at the University of Southampton. The University of Southampton is one of the UK’s leading research-intensive universities, regularly exceeding £100M per year in research funding. The successful applicant will become part of a vibrant interdisciplinary community of researchers within the Institute for Life Sciences (https://www.southampton.ac.uk/life-sciences/index.page) combining theoretical and experimental methods to a range of problems in the life sciences. Prof. MacArthur has academic positions in both the Faculty of Medicine and Mathematical Sciences and runs both experimental and theoretical research programmes. He is a Fellow of the Alan Turing Institute (ATI), the UK national institute for data science and artificial intelligence based in the British Library, London. The successful applicant will benefit from strong association with the ATI research community, and will be expected to visit the ATI regularly.

This is a challenging project that will require knowledge of advanced machine learning as well as modern cell and molecular biology. The successful candidate will have a PhD* degree in Mathematics, Bioinformatics, Computer Science, Physics or related field, with a background and/or demonstrated interest in molecular/cellular biology and machine learning. Programming experience in a numerical computing environment such as R, python or MATLAB is essential. An enthusiasm for real-world applications of complex mathematical ideas and a positive attitude towards interdisciplinary research is also essential. Experience with single cell sequencing data is desirable.

The position is for a fixed term of 12 months, although it is expected that this Pilot Project will lead to further funding.

 Informal inquiries may be made via email to Professor Ben MacArthur (bdm@soton.ac.uk).

*Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification.  The title of Research Fellow will be applied upon successful completion of their PhD.  Prior to the qualification being awarded the title of Senior Research Assistant will be given.

Application Procedure: 

You should submit your completed online application form at https://jobs.soton.ac.uk. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Hannah Farrance (Recruitment Team) on +44 (0) 23 8059 2507. Please quote reference 1227420AF on all correspondence.

The Faculty of Medicine holds an Athena SWAN Silver Award demonstrating commitment to equal opportunities and gender balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. For further information including key benefits designed to help maintain and support employees' well-being and work-life balance, please see our working with us website pages.  

The closing date for this job opportunity has now passed, and applications are no longer being accepted for this position

Further details:

We aim to be an equal opportunities employer and welcome applications from all sections of the community. Please note that applications from agencies will not be accepted unless indicated in the job advert.


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