Research Leader / Senior Scientist (Computational Drug Design), Cambridge, MA

Isomorphic Labs•Cambridge, MA

1d•Hybrid

About The Position

Isomorphic Labs is seeking a Research Leader or Senior Scientist in Computational Drug Design to join their interdisciplinary team. This role involves applying frontier AI to accelerate drug discovery and develop life-changing medicines. The company leverages AI models, including those building on AlphaFold, to predict and generate novel molecules, anticipate drug performance, and design innovative treatments for diseases. The Applied Computational Drug Design team works closely with machine learning colleagues, shaping and refining AI algorithms through computational chemistry expertise. This position offers an opportunity to provide scientific expertise and strategic direction for drug discovery projects, guide them towards clinical candidate selection, and enhance the AI platform. Some roles may include people management responsibilities, including line managing and mentoring a team of Computational Chemists, fostering a supportive culture of continuous learning and adoption of next-generation tools.

Requirements

PhD in Computational Chemistry, or a related scientific field, or equivalent industrial experience.
8+ / 5+ years of professional experience in a Computational Drug Design role, operating within a biotech, pharma or CRO setting.
Proven track record of project leadership / leading computational chemistry efforts on drug discovery programs, demonstrating significant contributions to project progression (ideally from hit identification through to lead optimisation or candidate nomination).
Expertise in writing and implementing Python scripts for analysis and tool development, and/or utilising pipelining tools to support cheminformatics and design workflows.
A genuine passion for drug discovery and enthusiasm for the potential of ML to transform the field.
For a people / program management position: experience of leading a high-performing scientific team, mentoring and empowering them to thrive in their roles.
Strong track record of scientific achievements, evidenced by publications, patents, and presentations.
Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
Track record of strategic thinking and creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice To Haves

Prior experience leveraging machine learning and generative AI methods for hit finding (e.g. ultra-large virtual screening and active learning), molecular design and lead optimisation (e.g. REINVENT, cofolding and AI-powered ligand/pose scoring methods).
Knowledge of other specific drug discovery approaches like fragment-based drug design (FBDD), and alternative modalities like PROTACs, molecular glues, PPI inhibitors or stabilisers, peptides etc.
Understanding of drug metabolism and pharmacokinetics (ADME + DMPK) principles.
Fluency in Python with ability to write code for new tools.
Track record of authorship of relevant scientific manuscripts and/or inventorship of composition of matter patents.
Experience working with or managing activities at contract research organisations (CROs).

Responsibilities

Apply AI-first approaches to provide technical and strategic directions, and execute drug design programs.
Take ownership as either an overall Program Lead or Computational Chemistry Lead.
Collaborate cross-functionally to support the data-driven delivery of high quality scientific solutions to complex technical problems.
Establish principles for embedding cutting-edge AI/ML into modern computational chemistry workflows, ensuring seamless integration across ML, Biology, and Chemistry teams.
Provide strategic input and technical direction to our ML platform teams.
If Program Leadership: Champion the drug discovery pipeline, overseeing external collaborations (with CROs) and leading programs to meet critical go/no-go milestones.
Prepare detailed scientific proposals and reports to support new and ongoing programs.
Embrace and champion our culture of inclusion and continuous professional development.
Line managing and mentoring a talented and high-performing team, encouraging their scientific growth and career development (for management roles).
Champion our cross-disciplinary approach, fostering a supportive team culture where continuous learning and the adoption of next-generation tools are the standard (for management roles).