Job Description
Job Description
Be a part of the legacy: Postdoctoral Research Fellow Program
Our Research Laboratories' Postdoctoral Research Fellow Program aims to be a best-in-industry program for industrial postdoctoral researchers, designed to provide you with an academic focus in a commercial environment. With the resources, reach, and expertise of a large pharmaceutical company, postdoctoral researchers will be positioned to excel in an institution committed to breakthrough innovation in research and discovery.
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The Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics (PDMB) function at research laboratories is seeking a highly motivated postdoctoral fellow with expertise in machine learning to help transform drug discovery and preclinical development. You will join an interdisciplinary team and collaborate closely with research partners across our global organization. You will invent, prototype, and apply advanced Machine Learning (ML) methods-particularly in generative modeling and related areas-to expand our capabilities in designing, prioritizing, and characterizing novel therapeutic candidates.
Primary Responsibilities
- Conduct original research to develop state-of-the-art AI/Machine learning methods for drug discovery (e.g., molecular generative models, multi-objective optimization, property prediction, active learning)
- Design and execute experiments, analyze results rigorously, and iterate rapidly on model architectures and training strategies
- Build robust, reproducible code and workflows; contribute to shared libraries and documentation
- Collaborate with chemists, biologists, Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics (PDMB) scientists, and data/ML engineers to translate methods into impactful applications
- Communicate findings through internal presentations and peer-reviewed publications; present at conferences and workshops
Education Minimum Requirements - Ph.D. (or completion within six months) in Computer Science, Statistics, Physics, Applied Mathematics, Bioinformatics, Computational Biology, Chem/Informatics, Engineering, or a related field
Required Experience and Skills - Demonstrated research excellence and problem-solving ability; strong motivation to learn, innovate, and deliver
- Proficiency in core ML/statistics topics such as probability, statistical inference, optimization, discrete math/algorithms, and/or probabilistic modeling
- Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
- Track record of publications and/or presentations in ML, computational chemistry/biology, or related fields
- Excellent collaboration and communication skills; proven ability to work in cross-functional teams
Preferred Experience and Skills (nice to have) - Experience with molecular representations (e.g., SMILES, graphs), generative models (e.g., diffusion models, VAEs, flow models), and sequence/structure models (e.g., transformers, GNNs, protein or RNA models)
- Familiarity with cheminformatics/biophysics toolkits (e.g., RDKit), docking or molecular simulation, ADMET modeling, or DMPK-relevant endpoints
- Practical experience with experimental design, active learning, uncertainty quantification, or multi-objective optimization
- Software engineering best practices (Git, testing, containers), and experience working with large datasets and cloud/GPU environments
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Employee Status: Regular
Relocation: Domestic
VISA Sponsorship: Yes
Travel Requirements: 10%
Flexible Work Arrangements: Hybrid
Shift: Not Indicated
Valid Driving License: No
Hazardous Material(s): N/A
Required Skills: Algorithms, Artificial Intelligence (AI), Computational Biology, Computational Chemistry, Computer Science, Electrical Engineering, Machine Learning, Physics, Statistical Inferences, Statistics
-Preferred Skills: Job Posting End Date: 10/7/2025
*A job posting is effective until 11:59:59PM on the day BEFORE -the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date. Requisition ID: R366327
Job Tags
Full time, Relocation, Visa sponsorship, Flexible hours, Shift work,