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Opportunity: Data Scientist -- Machine Learning -- Biomarker Discovery @ Company in Cambridge, UK
Submitted by Eugene McDaid; posted on Thursday, August 10, 2017
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RESPONSIBILITIES
A great opportunity has become available for a Data Scientist to join a company that are making ground-breaking progress in the world of epigenetics and genomics. The role focuses on providing insight into epigenomics experiments from clients and the post holder will develop computational tools and strategies to analyse epigenomic datasets. You will also be experienced with discovering biomarkers or developing tools for biomarker discovery (Machine/ DEEP Learning skills are a necessity) and providing deep analysis of complex data.
You will also develop bioinformatics tools and pipelines and explore new computational technologies as well as interacting with scientists and customers reach analysis goals.
REQUIREMENTS
Experience:
- You should have experience as a Data Scientist with a background in genomics/ bioinformatics/ epigenomics.
- You should also have an understanding of regulatory genomics/epigenomics and computational approaches in genetics.
- You will have a strong statistical background and enjoy working with algorithms and machine learning.
- An ideal candidate will have at least 3 years' experience within this field and including an MSc/PhD.
Required:
- Experience in working with NGS technologies as well as data generated from array based assays
- Very strong statistical knowledge and experience developing/implementing algorithms in relation to machine learning
- Strong skills in Python (SciPy), R, Perl
- Experience developing clinical bioinformatics applications
- DNA/RNA methylation – Desirable
- Cloud computing and knowledge of other programming languages such as Java/C++ – Desirable
HOW TO APPLY
Please do not hesitate to contact Harvey Uppal at huppal[at]pararecruit.com or call (+44) 121 616 3407 to discuss this opportunity further.
Keywords: Data Scientist, Bioinformatics, Genomics, Epigenomics, NGS, Biomarker Discovery, Statistics, Artificial Intelligence, Machine Learning, DEEP Learning, Algorithms, Python, Perl, Java, C++, DNA, RNA, Assays, Cambridge
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