UNIVERSITY OF SOUTHAMPTON

Research Fellow in Machine Learning

Location
Southampton, United Kingdom
Salary
£31,406 to £38,587 per annum
Posted
16 May 2022
End of advertisement period
02 Jun 2022
Ref
1811922PJ
Contract Type
Fixed Term
Hours
Full Time

Applied Mathematics & Theoretical Physics

Location:  Highfield Campus
Salary:   £31,406 to £38,587 per annum
Full Time Fixed Term until 30/09/2024
Closing Date:  Thursday 02 June 2022
Interview Date:   To be confirmed
Reference:  1811922PJ

You will join our team using artificial intelligence and mathematical modelling to examine the development of multimorbidity over the lifecourse as part of the MELD-B (Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity) research project. The post will be in the Applied Mathematics & Theoretical Physics group, which is part of the School of Mathematical Sciences at the University of Southampton.

MELD-B is an interdisciplinary project bringing together researchers in public health, statistical epidemiology, mathematical sciences and information systems to study the burden presented to patients by conditions such as heart disease, diabetes, asthma, depression and anxiety, along with their pattern of acquisition over patient lifetimes, in order to understand in greater detail how people develop complex and burdensome combinations of conditions and identify opportunities for effective intervention.

Your role will be to develop machine learning models for early-onset burdensome multi-morbidity, combining information from birth cohort and routine healthcare datasets to identify its early-life determinants. You will use a variety of methods to analyse the data, from off-the-shelf clustering algorithms and explainable AI, to developing semi-supervised learning approaches for matching across datasets, and exploring topological data analysis and graph-based learning.

To be successful you will have a PhD* or equivalent professional qualifications and experience in machine learning, topological data analysis, computational mathematical modelling or a closely related subject. In addition to machine learning research, an important part of the role is to interact with other MELD-B team members from a variety of different disciplinary backgrounds and to become familiar with multimorbidity research. Thus an interest and motivation in learning about multimorbidity research outside of your disciplinary expertise and the ability to communicate effectively across disciplinary boundaries are essential.

The School of Mathematical Sciences is committed to promoting equality, diversity and inclusion, and holds an Athena SWAN Bronze award. We welcome applicants from all sections of the community, regardless of gender, ethnicity, disability or sexual orientation, and will give due consideration to applicants seeking flexible working patterns and to those who have taken a career break. The University has a generous maternity policy** and onsite childcare facilities and offers a range of benefits designed to help maintain and support employees' well-being and work-life balance. The University of Southampton is committed to sustainability and being a globally responsible university and has been awarded the Platinum EcoAward.

*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 the PhD.  Prior to the qualification being awarded the title of Senior Research Assistant will be given.

This role is full time fixed term until September 2024 due to funding restrictions.

**subject to qualifying criteria

For informal enquiries before submitting your application, contact Prof Rebecca Hoyle (r.b.hoyle@soton.ac.uk).

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. Please include a covering letter, full CV and details of at least two referees in your application. If you need any assistance, please call Hannah Farrance (Recruitment Team) on +44 (0) 23 8059 2507. Please quote reference 1811922PJ on all correspondence.

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