Machine Learning Bioinformatician

Machine Learning Bioinformatician Oxfordshire

Oxford Nanopore Technologies
Full Time Oxfordshire 10.56 - 12.04 GBP Today
Job description

The Machine Learning Operations group at Oxford Nanopore Technologies is responsible for the engineering which enables training of ML models and their deployment in production.

About Us...

Oxford Nanopore Technologies is headquartered at the Oxford Science Park outside Oxford, UK, with satellite offices and commercial presence in many global locations across the US, APAC and Europe. Oxford Nanopore employs from multiple subject areas including nanopore science, molecular biology and applications, informatics, engineering, electronics, manufacturing and commercialisation. The management team, led by CEO Dr Gordon Sanghera, has a track record of delivering disruptive technologies to the market.

Oxford Nanopore's sequencing platform is the only technology that offers real-time analysis (for rapid insights), in fully scalable formats from pocket to population scale, that can analyse native DNA or RNA and sequence any length of fragment to achieve short to ultra-long read lengths.

Our goal is to enable the analysis of any living thing, by anyone, anywhere. We offer real-time nanopore-based DNA/RNA sequencing technology: accessible, easy to use and fully scalable for any requirement.

We are looking for an expert senior Bioinformatician within the ML Ops group to help enable detailed bioinformatics analysis within the wider ML Group.

The Machine Learning Operations group at Oxford Nanopore Technologies is responsible for the engineering which enables training of ML models and their deployment in production.

The Details...

Working with the Director of Machine Learning operations in:

Contributing to bioinformatics pipelines to enable the analysis of machine learning models produced by the ML group. This exciting time to join this new and growing team!

Using their bioinformatics knowledge to help ML engineers understand and interpret the biological relevance of their models and use relevant bioinformatics metrics to analyse their ML models.

Keeping up to date with the latest development in bioinformatics

Optimising the performance of bioinformatics pipelines used in production.

Mentoring junior employees and presenting their knowledge of bioinformatics to the wider ML group.

What We're Looking For...

You will hold at least a MSc (or equivalent experience) in Bioinformatics, Biology, Mathematics, Physics or a related subject area. You will have extensive experience with working with bioinformatics tools.

Ways to stand out:

  • A good track record and publications in Bioinformatics and/or machine learning.
  • Experience with workflow systems such as Snakemake, CWL and Nextflow
  • Experience with modern C++, Python and related programming languages.
  • Contributions to open source projects.
  • Familiarity with Natural Language Processing or time series analysis.

Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and abilities to perform the duties of the job.

Oxford Nanopore's goal is to bring the widest benefits to society through enabling the analysis of anything, by anyone, anywhere. The company has developed a new generation of nanopore-based sensing technology enabling the real-time, high-performance, accessible and scalable analysis of DNA and RNA. The technology is used in more than 100 countries to understand the biology of humans and diseases, plants, animals, bacteria, viruses and whole environments.

Oxford Nanopore was founded in 2005 as a spin-out from the University of Oxford and now employs over 1000 employees around the world.

Machine Learning Bioinformatician
Oxford Nanopore Technologies
Oxford, United Kingdom
Gordon Sanghera
Less than $1 million (USD)
51 to 200 Employees
Company - Private
Electronics Manufacturing
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