Computational Biologist, Tree of Life Genomics

Cultivarium; Greater London; On-site; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Paid time off

Private medical insurance

Employer pension contributions

Job summary

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.

Qualifications

• PhD in population genetics, evolutionary biology, computational biology, genomics, or related field.

Responsibilities

• Design and run pipelines for population- and comparative-genomic analysis across non-model organisms.
• Assemble, annotate, and curate genomes and pan-genomes for organisms with no reference.
• Analyze nuclear and organelle genome variation including heteroplasmy and cytonuclear interactions.
• Apply machine learning to predict gene function and trait architecture.
• Collaborate with wet-lab scientists to design experiments and produce reproducible code.
• Present work and mentor teammates, sharing computational-biology best practices.
• Maintain high standards and ownership within the team.

Skills

Population genomics

Variant calling

Annotation

Pipelines (Nextflow/Snakemake)

Python

R

Biopython

Bioconductor

Pandas

Git

GATK

bcftools

vcftools

PLINK

ANGSD

scikit-allel

Team collaboration

Education

PhD in population genetics or related field

Tools

GATK

bcftools

vcftools

PLINK

ANGSD

scikit-allel

Nextflow

Snakemake

Job description

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.