NextRaiseNextRaiseFind jobs
Sign inSign up free
Jobs / Process Engineer in United States of America
18 days ago
Apply with autofill
Apply with autofill
AstraZeneca·Pharma·18 days ago
18 days ago

Computational Chemistry Co-op , Closed-Loop Ligand Design and Optimization (Doctoral)

New Haven, United States of AmericaInternshipMid · 2-5 yearsProcess Engineer

Sign up free to see how well your resume matches this role.

Boost your chances at AstraZeneca

How you compare FREE

?
Your scoreYour score: not yet known
→
35
Top 10%Top 10%: 35 out of 100

Top 10% of NextRaise users matched against Process Engineer roles in United States.

Must-have skills for this role

  • synthetic organic chemistry
  • computational chemistry
  • dft calculations
  • quantum chemistry

PDF or DOCX · no account needed

Apply faster with autofill FREEThe NextRaise extension autofills your application in one click.careers.example.com/applyAutofillingFull namePriya SharmaEmailpriya.sharma@example.comPhone+49 30 1234567LocationBerlGet the extension

About this role

This is what you will do:
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. 
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.
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.

You will be responsible for:
•  Partnering with synthetic chemists to identify key selectivity challenges, co-design chemically reasonable training sets, and validate computational predictions against experimental outcomes.
• Performing DFT transition-state calculations to determine energies and geometries for a seed library of chiral ligands.
•  Developing machine learning surrogate models that predict diastereomeric ratios from molecular descriptors and implementing Bayesian optimization campaigns to sequentially identify optimal ligand candidates balancing selectivity, reactivity, and synthetic feasibility.
•  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.
•  Communicating scientific challenges and the technical approaches through regular updates and a final presentation.

You will need to have:
•  Currently enrolled in a Ph.D. program in synthetic organic chemistry or a related field with a focus on computational chemistry. 
• Practical experience with quantum chemistry-based calculations (such as DFT calculations), including transition-state theory and energy calculation workflows.
•  Hands-on laboratory experience in synthetic organic chemistry, catalysis, or a related area, including the ability to execute experiments safely and interpret experimental results.
• Understanding of organic stereochemistry and asymmetric catalysis concepts relevant to chiral ligand design.
• Understanding of Python (or other programming languages), including use of relevant scientific libraries.
• Foundational understanding of machine learning concepts: model training, validation, overfitting, and regression/classification frameworks.
• Strong written and verbal communication skills.
• Demonstrated ability to work collaboratively in a team environment and contribute to shared goals.
• A strong work ethic and high level of self-motivation with a strong desire to learn and contribute to shared project goals. 
• 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.
• 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.
 

We would prefer for you to have:
•  Prior experience in cheminformatics or data-driven research projects.
•  Prior experience with Bayesian optimization frameworks or active learning pipelines.
•  Familiarity with molecular descriptor generation, molecular fingerprints, or structure-activity/selectivity relationship modeling.
•  Experience with feature-attribution or model-interpretability methods applied to chemical or materials data.

Physical and Mental Requirements:
•  The duties of this role are generally conducted in an office environment. As is typical of an office-based role, you must be able, with or without an accommodation to: use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and non-linear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours. 

Compensation for this role is $48 per hour.

Date Posted

03-Sep-2026

Closing Date

05-Nov-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

Pharma

Company

AstraZenecaPharma
New Haven, United States of America

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from AstraZeneca's careers site·first seen 3 Sept 2026·last verified 8 Sept 2026·How we source jobs

Similar jobs

  • Engineer I: Process Engineer at globalhrGRAND PRAIRIE, United States of America–match not yet calculated
  • Continuous Improvement Quality Engineer at globalhrTUCSON, United States of America–match not yet calculated
  • Process Engineer - Day Shift at AstraZenecaCoppell, United States of America–match not yet calculated
  • Senior Director Process Engineering at abbvieNorth Chicago, United States of America–match not yet calculated
  • DMTS Process Development Engineer, Advanced Packaging at Micron TechnologyBoise, United States of America–match not yet calculated

Browse more jobs

  • Process Engineer jobs in United States
  • Manufacturing Engineer jobs in United States
  • Mechanical Engineer jobs in United States
  • Industrial Engineer jobs in United States
  • Process Engineer jobs in Germany
  • Process Engineer jobs in Singapore