Computational Biologist, Tree of Life Genomics

Computational Biologist, Tree of Life Genomics

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Build genomic pipelines and turn sequence data into biological insights.
  • Company: Join Cultivarium, a leader in genomics with a collaborative lab culture.
  • Benefits: Gain hands-on experience, mentorship, and work in a dynamic environment.
  • Other info: In-person role in London with opportunities for career growth.
  • Why this job: Make a real impact in genomics while collaborating with passionate scientists.
  • Qualifications: Experience in population and comparative genomics; teamwork skills are essential.

The predicted salary is between 63000 - 77000 £ per year.

Cultivarium seeks a computational biologist to apply population and comparative genomics across non-model organisms.

You will build pipelines, annotate genomes, and integrate diverse datasets to turn sequence data into biological insights.

You’ll collaborate with wet-lab scientists, apply ML to gene function and trait architecture, and present findings while mentoring teammates in a fast-paced lab environment.

This is an in-person role in London, UK.

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Computational Biologist, Tree of Life Genomics employer: Cultivarium

Cultivarium is an exceptional employer for scientists passionate about eukaryotic genome engineering, offering a collaborative and innovative work culture in the heart of London. With a strong commitment to employee growth, we provide opportunities to refine your craft while contributing to meaningful scientific advancements, alongside competitive benefits such as private medical insurance and a robust pension plan. Join us to tackle the toughest challenges in biology and make a tangible impact on society.

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Contact Details:

Cultivarium Recruitment Team

We think you need these skills to ace Computational Biologist, Tree of Life Genomics

Population Genomics
Comparative Genomics
Pipeline Development
Genome Annotation
Data Integration
Machine Learning (ML)
Biological Insights