Computational Biologists/Data Scientists

🔒 Confidential Employer
Posted 3 May 2026
LOCATION
Norwich
TYPE
Full-time
LEVEL
Mid-Senior level
SALARY
£39,345 / year
CATEGORY
Science & Research
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Machine Learning Statistical Data Analysis Computational Biology Bioinformatics Systems Biology Artificial Intelligence Genomics Microbiome

FULL DESCRIPTION

Computational Biologists/Data Scientists

[Employer hidden — view at passion-project.co.uk] is hiring Computational Biologists/Data Scientists. Salary: £32,225 - £39,345 per year. Contract length: 12 months. Closing date: 21 October 2020.

About the Role

Applications are invited for Computational Biologists/Data Scientists to join the Norwich Bioscience Institutes on a joint venture with the Alan Turing Institute. The post holders will apply machine learning approaches to tackle key challenges in various areas of biology relevant to the Norwich Bioscience Institutes (such as food security, genomics, big data in biology, microbiome). Candidates can choose to be based in Norwich, but remote and/or flexible working is also encouraged. Candidates must be based in the UK and will be expected to attend in person for key events.

Ideal Candidate

Candidates should have a background in computational biology, systems biology, bioinformatics (ideally to PhD level) or an MSc in computer science, applied mathematics, computational physics, computational biology, or related discipline with experience applying machine learning and statistical approaches.

Additional Information

Salary on appointment will be within the range £32,255 to £39,345 per annum depending on qualifications and experience. Further information and details of how to apply can be found here, or contact the Human Resources team on [contact hidden] or [contact hidden] quoting reference 1003927. As a Disability Confident employer, we guarantee an interview to disabled applicants who meet essential criteria.

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