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Isomorphic Labs is hiring Research Leaders and Senior Scientists in Computational Drug Design to join the Applied Computational Drug Design team in Cambridge, MA. The company applies frontier AI to accelerate drug discovery, building on the Nobel-winning AlphaFold system to create predictive and generative AI models that transform how medicines are designed.
You will provide scientific expertise and strategic direction for portfolio drug discovery projects, guiding them from initiation through clinical candidate selection. Working alongside world-leading ML scientists, you will enhance the AI platform through your computational chemistry expertise and apply these improvements to drug design projects. You will operate as either a Program Lead (overseeing external collaborations with CROs and leading programs to critical milestones) or a Computational Chemistry Lead (providing technical direction on design workflows).
Some roles include people management responsibilities for teams of 2–3 computational chemists, where you will mentor and develop talent while fostering a culture of continuous learning and cross-disciplinary collaboration.
Key responsibilities include: applying AI-first approaches to execute drug design programs; collaborating cross-functionally on data-driven scientific solutions; establishing principles for embedding AI/ML into computational chemistry workflows; providing strategic input to ML platform teams; preparing scientific proposals and reports; and championing the company's inclusive culture.
The role requires 3 days per week in-office presence (Tuesday, Wednesday, and one additional day).
REQUIREMENTS:
Essential:
- PhD in Computational Chemistry or related scientific field, or equivalent industrial experience
- 8+ years (for Research Leader) or 5+ years (for Senior Scientist) of professional experience in Computational Drug Design within biotech, pharma, or CRO settings
- Proven track record of project leadership on drug discovery programs, with significant contributions from hit identification through lead optimization or candidate nomination
- Expertise in Python scripting for analysis and tool development, and/or pipelining tools for cheminformatics and design workflows
- Genuine passion for drug discovery and enthusiasm for ML's potential to transform the field
- For people/program management positions: experience leading high-performing scientific teams, mentoring and empowering them
- Strong track record of scientific achievements evidenced by publications, patents, and presentations
- Excellent written and verbal communication; ability to work effectively in cross-functional, collaborative environments
- Strategic thinking, creative problem-solving, growth mindset, adaptability, and eagerness to learn new concepts and techniques
Nice to have:
- Prior experience leveraging machine learning and generative AI methods for hit finding (ultra-large virtual screening, active learning), molecular design, and lead optimization (REINVENT, cofolding, AI-powered ligand/pose scoring)
- Knowledge of fragment-based drug design (FBDD) and alternative modalities (PROTACs, molecular glues, PPI inhibitors, peptides)
- Understanding of ADME and DMPK principles
- Fluency in Python with ability to write code for new tools
- Authorship of scientific manuscripts or inventorship of composition of matter patents
- Experience working with or managing CRO activities
