Computational Biology & Machine Learning Scientist - #1767399
Skills Alliance
Computational Scientist – Machine Learning & Immunology & BiologicsA 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 RoleAs 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 QualificationsPhD (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 Qualifications3+ 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
Diffusion models in molecular design
Graph ML in biomedical networks
Experience with GPU computing (cloud or HPC clusters).
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