Computational Biologist

JR United Kingdom; England; On-site; GBP 50,000 - 90,000; Full time

Job summary

Join a pioneering biotech firm as a Computational Biologist specializing in Immuno-Oncology. This role offers a unique opportunity to lead the development of unsupervised machine learning models that will revolutionize antigen discovery. You'll work alongside a dynamic team, integrating multi-omics data and collaborating with experimental scientists to drive innovative research. Ideal for those looking to expand their impact in a rapidly evolving field, this position promises career growth and the chance to mentor others as the team flourishes. If you're passionate about computational biology and eager to make a difference, this is the perfect opportunity for you.

Qualifications

• PhD in Computational Biology, Bioinformatics, or related field.
• Strong experience with multi-omics data integration.

Responsibilities

• Develop unsupervised machine learning models for antigen discovery.
• Collaborate with scientists to guide research direction.

Skills

Machine Learning

Bioinformatics

Python

R

Problem-Solving

Collaboration

Education

PhD in Computational Biology

PhD in Bioinformatics

PhD in Machine Learning

Tools

CrytoMAP

BamQuery

Job description

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Computational Biologist – Immuno-Oncology

Overview:

This is a unique opportunity for a driven computational biologist to shape the future of antigen discovery in a cutting-edge biotech environment. You'll play a key role in the development of unsupervised machine learning models using transcriptomic datasets to support target identification and product development.

As the team grows, this position offers a clear path into leadershiP, ideal for someone ready to expand their impact both scientifically and strategically.

Key Responsibilities:

• Develop and refine unsupervised machine learning approaches to analyse multi-omics data, with a focus on transcriptomics
• Collaborate closely with experimental scientists and bioinformaticians to integrate data and guide research direction
• Support internal and external teams with in-house tools such as CrytoMAP and BamQuery
• Contribute to antigen discovery pipelines and help define computational strategy
• Help grow and mentor the computational biology function as the team expands
• Stay current with emerging methods in computational immunology, machine learning, and applied bioinformatics

Ideal Background:

• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field
• Strong experience with multi-omics data integration, ideally within immunology or oncology
• Hands-on expertise in Python and/or R, and familiarity with common bioinformatics workflows
• Track record of developing ML-based models, in an unsupervised context
• Excellent problem-solving, communication and collaboration skills
• Experience in a biotech or translational research setting is highly desirable