Industrial PhD Position: We are offering a unique Industrial PhD position focusing on the integration of AI and molecular dynamics simulations to discover small molecule binders for challenging-to-drug proteins. This collaborative project involves AstraZeneca, Stockholm University, and Chalmers University of Technology, supported by the Data-Driven Life Science program. The successful candidate will work at AstraZeneca in Gothenburg, Sweden, and be part of the DDLS Research School, pursuing a PhD at Stockholm University.
Industrial PhD Position – Drugging the Undruggable
Summary Table
| Designation | Industrial PhD Student |
|---|---|
| Research Area | AI and Molecular Dynamics Simulations for Drug Discovery |
| Location | Gothenburg, Västra Götaland County, Sweden |
| Eligibility/Qualification | Master’s degree in relevant fields, experience with Linux, PyTorch, independence, and collaborative skills |
| Job Description | Conduct MD simulations, use AI for protein flexibility modeling, design potential binders, summarize findings for scientific dissemination |
| How to Apply | Submit applications by June 10, 2024 |
| Last Date for Apply | June 10, 2024 |
Designation
Industrial PhD Student
Research Area
Drugging the Undruggable: Bridging AI and Molecular Dynamics Simulations to Discover Small Molecule Binders for Difficult-to-Drug Proteins
Location
Gothenburg, Västra Götaland County, Sweden
Eligibility/Qualification
- Essential Requirements:
- Master’s degree in Chemistry, Biophysics, Biotechnology, Data Science & AI, or related fields
- Proficiency in Linux environment
- Experience with PyTorch or similar deep learning frameworks
- Demonstrated independence and excellent collaborative skills
- Professional approach and ability to analyze complex issues
- Desired Qualifications:
- Knowledge of statistical mechanics
- Experience in data science and machine learning
- Application of deep learning in life sciences
- Proficiency with GROMACS or similar molecular dynamics tools
- Strong programming skills, preferably in Python
Job Description
The candidate will:
- Perform molecular dynamics (MD) simulations to study protein flexibility
- Use deep learning models like diffusion models to analyze protein flexibility
- Identify druggable pockets on protein surfaces using deep learning models
- Design potential binders using the generative AI tool REINVENT
- Summarize findings in manuscripts for high-impact international conferences and scientific journals
How to Apply
Interested candidates should submit their applications by June 10, 2024. Applications will be reviewed on a rolling basis, so early submission is encouraged.
Last Date for Apply
June 10, 2024
Join us in pushing the boundaries of science to deliver life-changing medicines. AstraZeneca is committed to building an inclusive and diverse team. We welcome applications from all qualified candidates, regardless of background, ensuring compliance with all non-discrimination laws and regulations. Apply today to make a significant impact on patients’ lives.
