Retrosynthesis Researcher, Machine Learning

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.

As a member of our Machine Learning team, you'll work at the forefront of computational chemistry and AI, contributing to high-impact research with real-world applications in small molecule drug discovery and materials science.

Who will love this job

• 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 who's familiar with ML tools like PyTorch, TensorFlow, and JAX
• An excellent problem-solver who's comfortable working collaboratively in a multidisciplinary research environment

What you'll do

• 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

What you should have

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

We'd prefer to hire someone who has

• Familiarity with chemical reaction databases (e.g., Reaxys, USPTO, Pistachio)
• Knowledge of computer-aided synthesis planning (CASP) tools and retrosynthetic analysis software (e.g., AiZynthFinder, ASKCOS, IBM RXN)
• A background in graph-based learning, attention mechanisms, and transformer architectures applied to chemical data
• Familiarity with reaction condition prediction and reaction yield optimization
• Experience with Schrödinger Suite and LiveDesign
• 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.