Head of Computational Biology

Head of Computational Biology (Confidential Search)

US | Onsite (Life Sciences / AI x Biology environment)

We are supporting a confidential, well‑funded life sciences organization building next‑generation infrastructure for AI‑driven biological discovery. The company operates at the intersection of computational biology, large‑scale biological data, and AI systems designed to generate evidence‑based scientific insights.

We are seeking a Head of Computational Biology to define and lead the scientific and computational strategy behind how complex biological data is structured, interpreted, and translated into actionable insights.

This is a senior leadership role responsible for building the computational biology foundation of a platform that integrates multi‑modal biological data and supports large‑scale scientific reasoning.

You will work across biology, engineering, and AI teams to ensure that biological evidence generated by the system is rigorous, reproducible, and biologically meaningful.

This is a hands‑on leadership position with both strategic and technical depth.

• Define the computational biology strategy across discovery and translational research
• Design frameworks for integrating multi‑omics and biomedical datasets (genomics, transcriptomics, proteomics, clinical, literature, etc.)
• Build structured biological representations (ontologies, knowledge models, data standards)
• Develop validation and benchmarking frameworks for biological reasoning systems
• Identify uncertainty, conflicting evidence, and knowledge gaps across biological datasets
• Translate biological questions into computational workflows and scalable analytical systems
• Partner closely with AI/ML and engineering teams on scientific reasoning systems
• Establish data governance, provenance, and reproducibility standards
• Recruit, mentor, and lead a high‑performing computational biology team

• PhD or equivalent experience in Computational Biology, Bioinformatics, Systems Biology, Genetics, or related field
• Strong background in multi‑omics data analysis and biological data interpretation
• Experience with large‑scale biological datasets and knowledge systems
• Familiarity with statistical modeling, network biology, and ML methods in biology
• Ability to bridge biological concepts with computational implementation
• Experience leading scientific or computational biology teams
• Strong communication skills across scientific and technical audiences

• Drug discovery, precision medicine, or translational research
• AI/ML applied to life sciences
• Knowledge graphs, pathway analysis, or systems biology frameworks
• Biomarker discovery and validation
• Scientific literature mining / evidence synthesis systems
• Experience in biotech, pharma, or AI‑driven biology platforms
• Exposure to foundation models or LLM‑enabled scientific workflows

You will work closely with:

• AI/ML and platform engineering teams
• Data engineering and infrastructure groups
• Scientific advisors and domain experts
• External research and biopharma partners