Computational Biologist

Outpost; Greater London; Hybrid; GBP 55,000 - 70,000; Full time

Benefits offered by this job

Equity

Private medical & dental

Pension

Life insurance

Cycle to Work

Job summary

Outpost Bio is seeking a Computational Biologist to turn microbiome data into biological understanding. You will own computational studies and connect experimental measurements to model inputs.

The role can be based in London or Boston, with ownership of analyses and collaboration across the team. The ideal candidate has a PhD or Master’s with 3+ years' industry research, strong metagenomics experience, and proficiency in Python or R.

Qualifications

• PhD or Master’s + 3+ years of industry research.
• Hands-on analysis of metagenomic or 16S data.
• Statistical design and multiple testing concepts.
• Proficient in Python and/or R with reproducible code.
• Experience with comparative genomics or sequence-based methods.
• Ability to explain data support to non-specialists.
• Nice to have: LC-MS data processing or cloud analyses.

Responsibilities

• Run standard analyses on experiments and calibrate them against controls.
• Assess datasets for model training and document suitability.
• Integrate new data types into workflows with scientists’ guidance.
• Document assumptions behind computational tools.
• Develop and validate methods for 16S and metagenomic data.
• Investigate drug/chemical responses across donors and conditions.
• Collaborate with experimental and ML teams to refine hypotheses.
• Write reusable analysis code and communicate results clearly.

Skills

Python

R

Metagenomics

16S data

Statistics

Education

PhD in a relevant field

Master's + 3+ years industry research

Tools

Git

Linux

Nextflow

Snakemake

Job description

Computational Biologist

Application Deadline: 19 October 2026

Department: Informatics

Employment Type: Full Time

Location: London

Compensation: £55,000 - £70,000 / year

Description

Outpost Bio is building models of how microbial communities respond to drugs and other chemicals. We are looking for a computational biologist to turn microbiome data into biological understanding and methods our scientists can rely on. You will own computational studies and the scientific decisions that connect experimental measurements to model inputs.

We're hiring one person for this role, and they can be based in either London or Boston.

Here is our timeline for hiring this role:

• Now until October 19th: Accepting applications
• October 26th: Planned start for interviews

Responsibilities

• Run the standard analyses on each experimental screen, calibrate them against controls and reference data, and keep them consistent as throughput grows.
• Assess every dataset before it is used for model training and/or decision making for further experimentation. Investigate contamination, assay drift, protocol changes and batch structure, document what is and isn't fit to learn from, and feed that back to the wet lab.
• Bring new data types into the same workflows as the wet lab adds them, metagenomics and in-house mass spectrometry among them, under the guidance of the scientists who own those methods. Work with the Data Platform Engineer to make validated methods repeatable.
• Take the computational tools we have already built to the point where the team uses them routinely, and document the assumptions behind them.
• Develop and validate methods to analyze 16S and metagenomic data from our experiments, collaborators and public studies. Make assumptions, quality checks and limitations explicit.
• Investigate responses to drugs and other chemicals across donors, communities and experimental conditions, using statistical controls that separate biological effects from batch effects, sampling and other confounders.
• Work with experimental scientists to refine hypotheses and design controls, replication and follow-up experiments, and with our computational scientists and ML researchers to define biologically meaningful features and benchmarks and investigate where models fail.
• Contribute to existing research initiatives and propose your own in-silico questions as the data supports them. Write reusable analysis code and explain results clearly to colleagues with different scientific backgrounds.

Your background

• A relevant doctorate, or a master's degree plus at least three years of industry work. Evidence of independent research through papers, preprints or comparable scientific outputs.
• Hands-on experience analyzing metagenomic or 16S data, with a good understanding of microbial biology and the limitations of reference databases and functional annotations.
• Sound statistical reasoning, including experimental design, confounding, repeated measurements, multiple testing and the challenges of compositional data.
• Proficiency in Python and/or R, with experience writing reproducible analysis code using Git and Linux. Other people should be able to understand and rerun your work.
• Comparative genomics, pangenomes, enzyme or pathway annotation, or sequence-based methods.
• Experience working with experimental scientists. You can explain what the data supports, challenge an unsupported interpretation and propose a practical way to resolve uncertainty.
• Nice to have: hands-on LC-MS data processing; experience with microbial metabolism or drug biotransformation; biological machine learning, evaluation of learned representations, or large-scale analyses using cloud compute; building shared workflows with Nextflow or Snakemake, or contributing to community bioinformatics software.

Why Join Outpost Bio?

• You'll own real equity in what you build. We offer meaningful stock options because we believe the people building this company should share in what it becomes. We want teammates who think like owners, and we structure compensation to reflect that.
• Outstanding benefits. Private medical and dental with Bupa from day one, paid by Outpost, and dependents covered at 50%. Pension with a 3% employer contribution. Life insurance, income protection and critical illness cover, all employer paid. Cycle to Work scheme. 25 days holiday plus bank holidays, your birthday off, and a paid winter break between Christmas Eve and New Year.
• An ML Lab-in-the-Loop. Your work feeds directly into Outpost's AI platform, and the platform feeds back into the next experiment. The loop between the wet lab, the data and the models runs in days, not years, and you'll iterate inside it whichever side you sit on.
• How we work. Expected in the office Monday, Wednesday and Friday, with flexible hours around a 10am to 4pm core and up to two weeks a year working from anywhere. Home office stipend and company computer. We cover conference costs and want you presenting your work, and every quarter you get a budget for drinks or coffee to learn from peers at other companies.
• Small team, outsized reach. You're joining a small founding team backed by top-tier investors with deep connections across AI and bio. The science you do here will directly shape how pharma and consumer companies understand molecule and microbiome interactions.