Chiral Catalyst Design Co-op — Computational + ML

BioCT Innovation Commons; New Haven (CT); On-site; USD 55,000 - 78,000; Full time

Job summary

Alexion Pharmaceuticals in New Haven, CT is seeking a Ph.D. candidate for a 6-month co-op focused on data-driven chiral ligand design.

You will develop a closed-loop platform combining DFT, ML, Bayesian optimization, and experimental testing to accelerate catalyst optimization. You will collaborate with chemists to validate predictions, perform transition-state calculations, and communicate results through updates and a final presentation.

Qualifications

• Currently enrolled in a Ph.D. program in synthetic organic chemistry or a related field.
• Experience with quantum chemistry-based calculations (DFT) including transition-state theory.
• Hands-on lab experience in synthetic organic chemistry and catalysis.
• Understanding of stereochemistry and asymmetric catalysis related to chiral ligands.
• Proficiency in Python or similar programming languages.
• Foundational knowledge of machine learning concepts and model development.
• Strong written and verbal communication skills.
• Ability to work collaboratively in a team and contribute to goals.
• Commitment to the full 6-month term and standard business hours.
• US Work Authorization required; CPT possible; OPT sponsorship not provided.

Responsibilities

• Partner with synthetic chemists to identify selectivity challenges, co-design training sets, and validate predictions against experiments.
• Performing DFT transition-state calculations to determine energies and geometries for seed chiral ligands.
• Develop ML surrogate models that predict diastereomeric ratios from descriptors and implement Bayesian optimization campaigns.
• Test computational predictions experimentally and refine subsequent design cycles.
• Build, maintain, and document the closed-loop pipeline (DFT > ML > BO > Exp) for reproducibility and scalability.
• Communicate scientific challenges and approaches through updates and a final presentation.

Skills

Python programming

Machine learning basics

Data-driven research

Communication

Team collaboration

Problem solving

Self-motivation

Academic diligence

Availability for 6 months

US work authorization

Education

Ph.D. candidate in synthetic organic chemistry or related field

Tools

Python

DFT calculations

Bayesian optimization

Job description

Alexion Pharmaceuticals in New Haven, CT is seeking a Ph.D. candidate for a 6-month co-op focused on data-driven chiral ligand design.

You will develop a closed-loop platform combining DFT, ML, Bayesian optimization, and experimental testing to accelerate catalyst optimization. You will collaborate with chemists to validate predictions, perform transition-state calculations, and communicate results through updates and a final presentation.