
Research Fellow - AR3187
- St Andrews, Fife
- £38,784-46,049 per year
- Contract
- Full-time
Fixed Term: 16 months.The Schools of Biology and Computer Science seek applications for a Research Fellow position in Computational Biology. We are looking for an enthusiastic person with a PhD degree in computational biology, computer science, or statistics, with background and experience in deep neural networks, preferably with expertise in any of the following subfields: interpretable machine learning and complex network analysis. We will also consider candidates with a strong background in one or more of the following areas: population genomics, computer sciences, statistics, bioinformatics.The successful candidate will work on a project aimed at uncovering epistatic interactions underlying complex phenotypic traits. We aim to develop interpretable deep learning techniques to predict an individual's phenotype from genomic data and identify not only the genetic variants underlying the trait, but also their interactions. The performance of the algorithms will be evaluated with simulated data and applied to real data. This is an exciting interdisciplinary research project between the Schools of Biology (Oscar Gaggiotti and Nathan Bailey) and Computer Science (Juan Ye and Simon Dobson), which is funded by a grant from BBSRC. The successful candidate will be based at the School of Computer Science but will interact extensively with biologists. The contract is for 100% FTE for 16 months.The successful applicant will have (or be near to completion of) a PhD.The post is available for 16 months starting 1 December 2025 or as soon as possible thereafter.Employees of the University have access to a wide range of including:
- Annual leave of 34 days, plus 5 public holidays.
- Financial contribution to
- A hybrid working environment, including partial homeworking where appropriate and a range of family friendly policies.
- Staff discount scheme for local and national goods and services.
- Free staff parking, employee Carshare and Cycle to Work Schemes and subsidised local bus travel.
- Subsidised sports membership, reduced tuition fees on degree programmes for staff, access to training and development opportunities including LinkedIn Learning, access to library facilities, salary sacrifice scheme.
- A range of wellbeing initiatives including membership of
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