Thesis Work, 30/60 Credits - Advancing AI-Driven Mechanism-of-Action Prediction from Cell Painting Images: Expanding the DeepPheno Platform
AstraZeneca · Mölndal, Sweden · Global
Clinical Data Science
–
Not yet analysed
Demand50
Career growth70
Healthcare fit25
Remote potential10
5-year outlook
Thesis positions are typically stipend-based; post-thesis, AI roles in pharma offer competitive salaries, but exact figures vary by role and location.
Clinical license
Not required
Applicant reach
narrow
Seniority
entry
Employment type
full-time
Date found
2026-09-14
Intelligence details
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Sign in to startWhy this is worth applying to
This is a niche opportunity for clinicians who are also pursuing a master's in bioinformatics/data science and have strong Python/deep learning skills. It offers a direct entry into pharma AI, but most clinicians without these technical prerequisites should not apply.
Who should apply
Clinicians currently enrolled in an MSc program in bioinformatics, data science, AI, or related fields, with strong Python and deep learning experience, and an interest in drug discovery.
CV angle
Highlight clinical background as domain expertise in biology and drug mechanisms, and emphasize any computational coursework or projects involving Python, machine learning, or image analysis.
Skills to highlight
- Python
- PyTorch
- Deep Learning
- Image Analysis
- Biological Data Integration
- Drug Discovery Knowledge
- Machine Learning
Role summary
A master's thesis project at AstraZeneca to improve DeepPheno, an AI platform that predicts compound mechanisms of action from Cell Painting images, involving model development, data integration, and explainability.
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