Computational Biologist

ZipRecruiter; England; On-site; GBP 45,000 - 70,000; Full time

Job summary

An innovative biotech firm is seeking a Computational Biologist to lead the development of machine learning models for antigen discovery. This role offers a unique opportunity to work with cutting-edge technologies and collaborate closely with experimental scientists. The ideal candidate will possess a PhD in a relevant field and have hands-on experience with multi-omics data integration, particularly in immunology or oncology. As the team expands, this position provides a clear path to leadership, making it perfect for someone eager to make a significant impact in a dynamic environment.

Qualifications

• PhD in Computational Biology, Bioinformatics, or Machine Learning required.
• Strong experience with multi-omics data integration in immunology or oncology.

Responsibilities

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

Skills

Machine Learning

Python

R

Bioinformatics

Problem-solving

Education

PhD in Computational Biology

PhD in Bioinformatics

PhD in Machine Learning

Tools

CrytoMAP

BamQuery

Job description

Job Description

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