Molecular AI Scientist: Structure-Guided Drug Design

Takeda; Boston (MA); On-site; USD 116,000 - 182,000; Full time

Job summary

Takeda is seeking a Research Scientist to advance AI-enabled drug discovery, focusing on structure-guided small-molecule design. You will blend ML, structural biology, and medicinal chemistry to push the frontiers of chemical space exploration and translate insights into therapies.

Work with cross-disciplinary teams to create scalable computational workflows, benchmark rigorously, and publish findings in internal talks and external venues. Boston-based role with competitive compensation.

Qualifications

• Ph.D. in Computational Biology, Biophysics, Computer Science, Computational Chemistry, or a related field, with a research focus in ML for molecular modeling.
• Hands-on experience developing, training, and validating deep learning models, including architectures relevant to structural biology and chemistry.
• Direct experience with modern structure prediction or co-folding methods (e.g., AlphaFold2/3, RoseTTAFold, Chai-1, Boltz) or comparable molecular ML systems.
• Strong proficiency in Python and modern ML frameworks (PyTorch and/or JAX).
• Demonstrated scientific rigor the ability to design controlled experiments, interpret results critically, and iterate effectively on model development.
• Strong written and verbal communication skills, and the ability to collaborate in a fast-paced, multidisciplinary research environment.

Responsibilities

• Develop and iterate on deep learning models across the molecular modeling stack — structure prediction, protein–ligand co-folding, affinity, and/or generative design.
• Design and execute rigorous benchmarking and evaluation pipelines that connect offline metrics to real-world performance.
• Partner with senior scientists and engineers to integrate validated models into production-ready drug discovery workflows.
• Apply computational and data-analysis methods to structural and sequence datasets to generate insights that guide model development.
• Apply generative AI and predictive ML models to design and prioritize chemical matter for research projects.
• Communicate findings through internal scientific talks, technical write-ups, and peer-reviewed publications.
• Collaborate across multidisciplinary teams to prototype and scale impactful solutions.

Skills

Python

ML frameworks

Communication

Team collaboration

Education

Ph.D. in Computational Biology or related

Tools

PyTorch

JAX

Job description

Takeda is seeking a Research Scientist to advance AI-enabled drug discovery, focusing on structure-guided small-molecule design. You will blend ML, structural biology, and medicinal chemistry to push the frontiers of chemical space exploration and translate insights into therapies.

Work with cross-disciplinary teams to create scalable computational workflows, benchmark rigorously, and publish findings in internal talks and external venues. Boston-based role with competitive compensation.