Senior Scientist, Computational Chemistry

Magnet is a biotechnology company pioneering the discovery of oral molecular glues - small molecules that induce proximity between proteins to modulate their function. Our proprietary True Glue(TM) platform is designed to address hard-to-drug targets across cancer and immune-mediated diseases.

With support from ARCH Venture Partners, Newpath Partners, Taiho Ventures, and Eli Lilly, Magnet is advancing internal programs in oncology, immunology, and inflammation. Magnet has also entered into a collaboration and license agreement with Eli Lilly to discover, develop, and commercialize specific molecular glue therapeutics in oncology.

We are seeking a highly motivated and hands-on Computational Chemist to join our team. In this role, you will apply cutting-edge computational methods and AI/ML approaches to accelerate drug discovery from hit identification through clinical candidate nomination. You will be a key contributor to our molecular glue platform, working at the intersection of structure-based design, cheminformatics, and data science to drive the DMTA cycle forward.

This is a highly collaborative role that requires both deep technical expertise and the ability to translate scientific questions into actionable strategies across multidisciplinary teams.

• Apply ligand-based and structure-based drug design approaches (including molecular dynamics simulation, TI/FEP+, water analysis, protein dynamics, etc) to enable hypothesis-driven compound design and reaction-based library design.
• Partner closely with medicinal chemists, biologists, biophysicists, protein scientists, proteomics, DMPK, and informatics teams to support early discovery and pipeline programs.
• Communicate findings clearly and compellingly to both technical and non-technical audiences across all levels of the organization.
• Build and maintain computational tools, workflows, AI/ML models, and databases for the processing and analysis of complex drug discovery datasets, including DNA-encoded library (DEL) data analysis, DEL library construction, druggability evaluation, target/presenter gluability and ADMET prediction.
• Analyze and interpret experimental data (such as ternary and binary biochemical, biophysical and cellular assay data, X-ray/Cryo-EM structures, XL-MS/HDX/NMR, DEL data, proteomics screening) to generate actionable insights that guide project decisions and impact the design‑make‑test‑analyze (DMTA) cycle.
• Drive development and implementation of novel computational methodologies — including AI/ML, data exploration, and visualization to strengthen and expand our molecular glue discovery platform.
• Manage and maintain R&D software platforms including Vortex, Schrödinger Suite (Maestro, Live Design, PyMOL), MOE, and RESTful APIs.

Required

• Ph.D. in Computational Chemistry, Cheminformatics, Chemistry, Computer Science, Data Science, or a related field, with 5-8 years of experience in life sciences; or equivalent combination of education and experience.
• Demonstrated expertise in ligand-based and structure-based computational drug design and optimization.
• Hands‑on experience with Vortex, Schrödinger Suite (Maestro, Live Design, PyMOL), MOE, and/or AWS, and familiar with AMBER, Gromacs, NAMD, VMD.
• Excellent written and verbal communication skills, with a proven ability to present complex scientific concepts to diverse audiences.
• Ability to manage multiple priorities independently in a fast-paced, dynamic environment.
• Proficiency in Python and relevant cheminformatics/data science packages (e.g., RDKit, Scikit‑learn, Pandas, Num Py); comfort working in a Linux environment.
• Strong analytical and problem-solving skills with the ability to derive meaningful insights from complex,…