Computational Biology & Machine Learning Scientist

JR United Kingdom; Stoke-on-Trent; On-site; GBP 40,000 - 65,000; Full time

Job summary

A cutting-edge biotech organization in Stoke-on-Trent seeks a Computational Biology & Machine Learning Scientist to engineer the immune system through innovative machine learning and statistical models. The role involves developing methodologies for analyzing complex biological data and collaborating across academic and clinical domains.

Qualifications

• PhD or MSc in relevant field with demonstrated ML experience.
• Strong background in ML, statistical modeling, and scientific productivity.
• Hands-on experience in biological data analysis and visualization.

Responsibilities

• Design and implement advanced machine learning models for biomedical challenges.
• Develop computational methods for biological sequence analysis.
• Drive ML-based pipelines for diagnostic or therapeutic design.

Skills

Machine Learning

Statistical Modeling

Data Handling

Visualization

Biological Data Analysis

Collaboration

Education

PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or Physics

MSc with equivalent experience

Tools

Python

TensorFlow

PyTorch

GPU Computing

Job description

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Computational Biology & Machine Learning Scientist, stoke-on-trent

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Client:

Skills Alliance

Location:

stoke-on-trent, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

4

Posted:

06.06.2025

Expiry Date:

21.07.2025

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Job Description:

Computational Scientist – Machine Learning & Immunology & Biologics

A cutting-edge biotech organization is seeking highly motivated Computational Scientists to support the mission of decoding and engineering the immune system. The role focuses on developing advanced machine learning and statistical models to analyze complex biological data, particularly immune repertoires and multimodal datasets.

About the Role

As part of a collaborative Computational Biology team, you will:

• Design and implement machine learning models—particularly language models, diffusion models, or graph neural networks—tailored to biomedical challenges.
• Build novel computational methods for interpreting biological sequences and structural data.
• Customize existing tools and develop new ones for integrative analysis and visualization of large-scale systems immunology data.
• Drive ML-based pipelines for diagnostic or therapeutic design.
• Benchmark computational methods and optimize performance across datasets.
• Lead or contribute to collaborative projects spanning academic, clinical, and industry domains.

Required Qualifications

• PhD (or MSc with equivalent experience) in Computational Biology, Bioinformatics, Computer Science, Statistics, Physics, or related quantitative discipline.
• Strong background in machine learning and statistical modeling, with a demonstrated ability to solve complex biological problems.
• Proven track record of scientific productivity (e.g., peer-reviewed publications).
• Hands-on experience in data handling, visualization, and biological data analysis.
• Proficient in Python, familiar with software development best practices.
• Practical experience with TensorFlow and/or PyTorch.

Preferred Qualifications

• 3+ years post-graduate experience in academia or biotech/pharma, applying ML/AI to biological datasets.
• Prior exposure to immunology, especially TCR/BCR repertoire analysis, or experience with protein design & or biologics.
• Deep expertise in at least one of the following areas:
• Language models for sequence analysis
• Graph ML in biomedical networks
• Experience with GPU computing (cloud or HPC clusters).