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The Oxford Biomedical Data Science Training Programme, funded by Wellcome and the Oxford Biomedical Research Centre, is designed to train biomedical scientists in the skills and methods required for the analysis and interpretation of large-scale biomedical datasets, particularly genomic and functional genomic data.

Training 1

This unique programme runs three times per year, with timings aligned to the University of Oxford terms. Numbers are limited and application is through a competitive process. The application schedule for 2019 can be found below. Training takes the form of six weeks of group lectures, tutorials and exercises, followed up with weekly code clinics. The programme is open to all University of Oxford staff and D.Phil. students and costs £6000.

Three scholarships per cohort have been generously funded by the Precision Medicine Cluster of the Oxford NIHR Biomedical Research Centre. Places will be awarded by a review committee based on the scientific quality of the proposed project and training needs of the individual. To be considered for a BRC scholarship, projects must fall within the remit of the NIHR, which funds research for patient benefit, and must focus on analysis of human samples. Priority will be given to applicants in research groups affiliated with one of the five themes of the BRC Precision Medicine Cluster, namely Multi-modal Cancer Therapies, Molecular Diagnostics, Genomic Medicine, Respiratory, and Haematology and Stem Cells. However, applications from all BRC Themes will be considered if there are sufficient spaces available. Details of all BRC Themes are available on the Oxford BRC website

 To apply please fill in this form and email it to

Training Schedule




Managing your software environment (Conda)

Navigating file systems, managing processes, manipulating text files, running genomics tools


Basic programming concepts, code organisation, algorithm design, debugging.

Advanced Python

Version control, object-oriented programming, Python for computational genomics, Python for data science (pandas)

Genomics pipelines

High performance computing, automating workflows in Python, genomics pipelines: RNAseq, ChIP-seq, ATAC-seq, single-cell RNAseq

Interpretation of genomic data

Enrichment analysis, pathway analysis, network analysis

R & Statistics

R syntax and data structures, Tidyverse, differential gene expression, pathway analysis, PCA, clustering

Machine Learning

Linear regression, random forests, deep learning


Course Dates

Cohort Applications Open Applications close Course starts Course Ends
September 2019 Closed Closed 16/09/2019 25/10/2019*
January 2020 12/09/2019 21/10/2019 06/01/2020 14/02/2020*

 * Course dates cover initial 6 week training period only