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Postdoctoral Research Assistant in Machine Learning, Bioinformatics and Genome Editing

University of Oxford - Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, John Radcliffe Hospital

Location: Oxford
Salary: £36,024 to £44,263 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 5th June 2024
Closes: 2nd July 2024
Job Ref: 173222

We are seeking a highly motivated and enthusiastic Postdoctoral Research Assistant to join  Professor James Davies’ Laboratory. The post will involve working on a project to develop deep neural network based methods for designing genome editing strategies to treat rare diseases.

The postholder will join a large multidisciplinary team covering molecular methodologies, genomics, single cell genomics/transcriptomics, computational biology and machine learning. The overarching aim of the project is to develop strategies to treat patients with rare genetic disorders at scale.  Duties will include assisting with the development of software and algorithms for the prediction of genome editing strategies at scale and to develop deep neural network models to assist in identification of the most effective editing strategies and to select disease variants. 

Applicants should hold a relevant PhD (or be close to completion - thesis submitted at time of application) in Computational Biology, Bioinformatics, Computer Science, or related discipline. The successful candidate will possess a strong background in Biology, Statistics/Mathematics and/or Computer Science. Extensive experience in software and algorithm development is essential. Proficiency in Python for data analysis, NGS bioinformatics, and applied machine learning techniques is essential.  

This position is available fixed-term for 12 months, funded by the NIHR Biomedical Research Centre (BRC). Applications for this vacancy are to be made online.

You will be required to upload a CV and supporting statement as part of your online application.

The closing date for this position is 12.00 noon on Tuesday 2 July 2024.

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