Computational Biologist/Bioinformatician

  • Published:

Provide expertise, tools, infrastructure, and analysis that underpins TSL's high impact science.

The Sainsbury Laboratory (TSL) is searching for a dynamic, motivated individual to work in an exciting bioinformatics/computational biology/data science focussed team. As a successful applicant you will be able to make the most of and expand your knowledge in the domains of computational biology and data science as it applies to the laboratory’s work in high throughput sequencing, proteomics, genomics, high throughput imaging and other data intensive techniques.

The Bioinformatics team at TSL provides expertise, tools, infrastructure, and analysis underpinning all the high impact science at TSL and provides teaching and training to postgraduates and postdoctoral scientists through contributions to an MSc and through internal training courses. You will become involved in a range of challenging and important projects in research, software engineering, bioinformatics and teaching/training. Your role will not be service provision but will centre on being a fully collaborative scientist working on challenging projects across the groups of the laboratory.

As the person appointed you will take responsibility for designing and executing computational biology and data science experiments in direct collaboration with other scientists in the laboratory. You will develop and deliver short, domain specific training workshops and lectures. You will work closely with and report to the Head of Bioinformatics and you will be expected to take a strong experimental lead and develop analyses and pipelines as the projects you work on proceed.

You will find opportunities to develop and release software tools and packages that arise as part of this work, and you will be able to develop skills in training and deliver short – medium length training courses within the institute

You will have (or be working towards)

  • a PhD in a bioinformatics/computational biology related field with broad knowledge of plant biology, molecular biology, microbiology, genetics, or a related field.
  • a good understanding and experience with Python/R or similar
  • a good knowledge of working with some form of high-performance computing cluster
  • a good knowledge of genomics techniques and tools for assembly, SNP calling and transcriptomics
  • skill in producing reproducible analyses and pipelining tools e.g snakemake

You may also have

  • experience in image analysis
  • experience in proteomics formats and analysis
  • understanding of common public databases e.g ENA,
  • experience with teaching or training biologists in computational skills
  • experience with basic admin of workflow tools e.g Galaxy

Salary will be within the TSL Research & Analogous Staff Grade 7 scale at between £38,784 - £46,049pa gross. However, the appointment level will reflect qualifications, skills, knowledge and achievements. This is a FULL-TIME (37 hours per week), Indefinite contract, mainly on site (flexible working can be requested, but the role will mainly be on site), this has a 6 month probationary period.

The Sainsbury Laboratory (TSL) is a world leader in plant and microbial science that is dedicated to making fundamental discoveries in the science of plant-microbe interactions. TSL has expanded its scientific mission not only to continue providing fundamental biological insights into plant-pathogen interactions, but also to deliver novel, genomics-based solutions that will significantly reduce losses from major crop diseases, especially in developing countries.

We offer 30 days annual leave, a generous pension scheme and the opportunity to develop skills and knowledge. We are located on an attractive campus offering cultural and recreational activities. We are committed to creating and promoting a diverse and inclusive workforce and we provide a supportive working environment for all colleagues.

If you wish to discuss this vacancy, please contact the HR Department: HR@tsl.ac.uk

Please apply online via this page by clicking 'Apply Now' and quote reference code DMc01/2026. Applicants should provide a CV, including the names and contact details of two or more referees, and a covering letter of no more than one A4 addressing the selection criteria.

Ref: DMc01/2026

Closing date: 2nd November 2026