AstraZeneca
Computational Chemistry Co-op , Closed-Loop Ligand Design and Optimization (Doctoral)
US - New Haven - CT · Intern · Internship
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About the role
- SPD is a multidisciplinary team of scientists supporting synthetic drug substance, drug product, and analytical development across Alexion's synthetic portfolio, spanning preclinical development through commercial launch.
- If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.
Responsibilities
- Alexion's Synthetic Product Development (SPD) team is seeking a highly motivated graduate student currently enrolled in a Ph.D. program in synthetic organic chemistry or a related field, with an interest in data-driven catalyst design, for a 6-month co-op program in 1H 2027.
- This co-op will focus on developing a closed-loop computational and experimental platform that integrates state-of-the-art computational tools and experimental testing to accelerate chiral ligand development and optimization.
- This position offers a unique opportunity to gain hands-on experience in applying computational chemistry and AI technologies to real-world challenges in diastereoselective catalyst design, ligand discovery, and computationally guided experimental optimization.
- Partnering with synthetic chemists to identify key selectivity challenges, co-design chemically reasonable training sets, and validate computational predictions against experimental outcomes.
- Testing computational predictions experimentally and using the resulting data to refine subsequent design cycles.
- Building, maintaining, and documenting the closed-loop computational pipeline (DFT → ML → BO → Exp) to ensure reproducibility, scalability, and knowledge transfer to the broader SPD team.
- Understanding of organic stereochemistry and asymmetric catalysis concepts relevant to chiral ligand design.
- This role does not provide OPT sponsorship or support. Candidates authorized to work under CPT may be considered, subject to verification of eligibility and applicable company requirements.
- 05-Nov-2026 Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees.
Requirements
- As is typical of an office-based role, you must be able, with or without an accommodation to: use a computer
- Practical experience with quantum chemistry-based calculations (such as DFT calculations), including transition-state theory and energy calculation workflows.
- Must be available during the full 6-month term and maintain general availability during standard business hours.
- US Work Authorization is required at time of application.
- Experience with feature-attribution or model-interpretability methods applied to chemical or materials data.
Compensation
- for this role is $48 per hour.
Benefits
- Foundational understanding of machine learning concepts: model training, validation, overfitting, and regression/classification frameworks.
- Prior experience with Bayesian optimization frameworks or active learning pipelines.
Visa & Work Authorization
- US Work Authorization is required at time of application.
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