Principal Computational Scientist - Discovery Biology N & I (Billerica MA)

Your Role:

We are seeking an experienced computational biologist to drive translational target discovery and disease understanding in neuroscience and immunology, with a strong focus on functional genomics and human disease biology. This role will connect human genetics and patient-derived multi-omics data with experimental model systems and predictive disease modeling to support target identification, validation, and prioritization across the discovery pipeline.

 As a Principal Scientist, Computational Biology – Functional Genomics within the Research Unit Neuroscience & Immunology (N&I), you will work at the interface of human genetics, computational biology, functional genomics, and translation, in close collaboration with bench scientists, disease area biologists, computational genetics colleagues, and cross-functional drug discovery teams. You will interpret genetic findings in biological context, generate mechanistic hypotheses, prioritize targets, and help guide the design and interpretation of perturbation-based experiments in disease-relevant systems.

 A central part of the role is to help connect human disease biology to experimental validation and back again. You will translate human genetics and patient-derived multi-omics into testable functional hypotheses, help identify relevant preclinical model systems, and integrate perturbation and omics data from those models back with human datasets to assess translational relevance, refine disease mechanisms, and strengthen confidence in downstream clinical success.

 You will integrate diverse data types — including human genetics, transcriptomics, proteomics, imaging, perturbation datasets, and single-cell or spatial omics where relevant — to uncover disease mechanisms and build scalable computational approaches for target validation and prioritization. You will contribute to predictive models of disease biology and perturbation response using systems biology, network analysis, and AI-enabled methods, with applications in disease modeling, patient stratification, disease endotyping, and therapeutic hypothesis prioritization. In partnership with cross-functional teams, you will also help integrate evidence on translatability, safety and toxicity risk, druggability, and modality considerations to support portfolio decisions.

Who You Are

 Minimum Qualifications:

• PhD in Computational Biology, Bioinformatics, Systems Biology, Biophysics, Data Science, or a related quantitative discipline, or in Biology, Medicine, Neuroscience, Immunology, or a related life science field with substantial specialization in computational biology
• Significant postdoctoral and/or industry experience, including relevant experience in pharma or biotech drug discovery

 Preferred Qualifications:

• Strong experience in computational biology applied to target discovery, functional genomics, translational biology, or disease modeling
• Experience interpreting human genetics and patient-derived multi-omics data to generate mechanistic hypotheses and support target identification or validation
• Experience integrating complex datasets, including combinations of transcriptomics, proteomics, perturbation data, imaging, genetics, and single-cell or spatial omics
• Good understanding of how to connect human disease biology with preclinical model systems, including assessing translational relevance and supporting model