Thesis Work, 30 Credits - Advancing AI for Drug Discovery with MolecularAI at AstraZeneca
AstraZeneca · Mölndal, Sweden · Global
Health Tech
–
Not yet analysed
Demand75
Career growth80
Healthcare fit20
Remote potential–
5-year outlook
Thesis work is typically unpaid or credit-based; however, skills in AI/ML drug discovery are in high demand and can lead to competitive computational R&D roles, though exact salaries vary by market and experience.
Clinical license
Not required
Applicant reach
narrow
Seniority
entry
Employment type
full-time
Date found
2026-10-03
Intelligence details
Flexible work details
- Engagement type
- Permanent
- Hours
- Full-time
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Only consider if you are enrolled in a relevant MSc program and want hands-on AI drug discovery experience; it is not a clinical career pivot or a paid non-clinical job.
Who should apply
MSc students in computer science, machine learning, AI, cheminformatics, or computational chemistry, including clinicians who have transitioned into such a master's program.
CV angle
Highlight Python programming, machine learning projects, data science, molecular modeling/cheminformatics coursework, and any research or thesis work; for clinicians, frame clinical data analysis, statistics, and research experience as transferable computational skills.
Skills to highlight
- Python
- Machine Learning
- Deep Learning
- Molecular Simulation
- Cheminformatics
- Data Science
- Reinforcement Learning
- Drug Discovery
Role summary
Master's thesis project (30 credits) at AstraZeneca's MolecularAI group, developing AI/ML methods for drug discovery, including molecular design, synthesis prediction, simulation, and property prediction. On-site in Gothenburg, Spring 2027.
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