Retrosynthesis Researcher, Machine Learning

Retrosynthesis Researcher, Machine Learning

Location:

New York

Schrödinger seeks a Retrosynthesis Researcher in Machine Learning (ML) to join us in our mission to transform the discovery of therapeutics and materials.

Schrödinger has pioneered a physics-based software platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is used by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Our multidisciplinary drug discovery team also leverages the platform to advance collaborative programs and its own pipeline of novel therapeutics to address unmet medical needs.

• An ML expert who has applied AI tools to chemical reaction prediction or retrosynthesis (e.g., reaction templates, template-free approaches) and understands organic synthesis and reaction mechanisms.
• An experienced user of cheminformatics tools (e.g., RDKit, Open Babel).
• A proficient Python programmer familiar with ML tools like PyTorch, Tensor Flow, and JAX.
• An excellent problem-solver comfortable working collaboratively in a multidisciplinary research environment.

• Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic pathway prediction.
• Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions, and identify novel synthetic routes.
• Curate and manage reaction datasets from literature, patents, and proprietary sources to train and validate predictive models.
• Integrate retrosynthesis tools with cheminformatics platforms and molecular modeling software.
• Collaborate with synthetic chemists to experimentally validate predicted retrosynthetic routes and optimize laboratory workflows.
• Contribute to scholarly publications in high-impact journals and represent the research group in conferences and workshops.

• PhD in Chemistry, Computational Chemistry, Cheminformatics, or a related field.
• A solid publication record that demonstrates expertise in retrosynthesis algorithms and computational chemistry.

• Familiarity with chemical reaction databases (e.g., Reaxys, USPTO, Pistachio).
• Knowledge of computer-aided synthesis planning (CASP) tools and retrosynthetic analysis software (e.g., Ai Zynth Finder , ASKCOS, IBM RXN).
• A background in graph-based learning, attention mechanisms, and transformer architectures applied to chemical data.
• Experience with reaction condition prediction and reaction yield optimization.
• Experience with Schrödinger Suite and Live Design.
• Experience with de novo design and generative machine learning methods.
• Experience with cloud computing and/or high-performance computing (HPC) resources.
• Exposure to quantum chemistry (DFT) is a plus.

Estimated base salary range: $120,000 - $145,000. The actual compensation package depends on factors such as experience, education, and business needs. It includes a competitive salary, equity-based compensation, and a wide range of benefits including healthcare (with dental and vision), a 401(k), pre‑tax commuter benefits, a flexible work schedule, parental leave, paid vacation, and regular catered meals.

Schrödinger is an equal‑opportunity employer that hires outstanding individuals into every position. We do not discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or other protected characteristic. We are committed to creating a safe environment where our employees can grow and contribute, and we provide reasonable accommodations for employees who require them.

Sound exciting? Apply today and join us!