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Bioinformatics Data Scientist

Business Type: Academia, Biotechnology Company
Job Type: Genomics, Statistic - Biostatistics, Bioinformatics
Job Level: Experienced (non manager)
Position: Full Time
Location: London
Reference: GELDataSci
Closing Date: 01/12/20
Job Details:
Bioinformatics Data Scientist
Location: Cambridge or London (initially remote due to Covid-19)

Following the successful completion of one of the largest genomic projects the world has ever seen - the 100,000 Genomes Project - Genomics England are expanding on an ambitious new venture that seeks to sequence the whole genomes of 5 million patients within the next five years. This revolutionary government-funded initiative has produced a wealth of data that could provide crucial insights into rare diseases and cancers, revolutionising healthcare and unlocking a new generation of treatments and diagnostic options that were never before possible.

We are now seeking a talented Data Scientist to join our team of expert Bioinformaticians, and support in developing innovative advanced statistical and machine learning approaches to analyse complex omics data-sets.

The ideal candidate will have:

-A PhD in a quantitative discipline such as Statistical Genetics, Mathematics, Physics or similar or equivalent work experience
-Familiar with a wide range machine learning methods, such as: neural networks, random forests, SVMs, regression, clustering, dimensionality reduction or ensemble methods
-Strong programming ability, proficient with Python, R or similar
-Previous experience of analysing large human genomic datasets is essential
-Experience of working with clinical data-sets would be a plus
-An understanding of rare diseases or cancer biology would be beneficial

On offer is a competitive salary package, stimulating projects and a fast-paced work environment. If you would like to find out more about this fantastic opportunity, send your CV to, or call Emilie for an informal chat on 0121 616 3477.

Key words: Data Science, Machine Learning, Genomics, Personalised Medicine, Human Genetics, Statistical Genetics, Quantitative Biology, London, Cambridge, Cancer, Rare Disease

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Posted: 03/11/2020 | NPJ Ref: 260587
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