Are you passionate about AI and its applications in drug discovery? Join AstraZeneca’s MolecularAI group for a master’s thesis project focused on advancing state-of-the-art machine learning, molecular simulation, and data science methods. Several projects are available, covering areas such as agentic AI, synthesis and reactivity prediction, molecular design, simulation, uncertainty-aware reinforcement learning, and molecular foundation models. Projects may be tailored to your interests and could involve collaboration with experimental and computational chemistry teams.

About AstraZeneca

AstraZeneca is a global, science-led, patient-centred biopharmaceutical company focusing on discovering, developing, and commercialising prescription medicines for some of the world’s most serious diseases. But we’re more than a global leading pharmaceutical company. At AstraZeneca, we're dedicated to being a Great Place to Work and empowering employees to push the boundaries of science and fuel their entrepreneurial spirit.

About the Opportunity:
As a Thesis Worker at AstraZeneca, you’ll find an environment that’s full of unique opportunities and exciting challenges. Here, you’ll have the opportunity to pursue your areas of interest whilst equally developing a broad skillset and knowledge base to get the best out of your experience. You’ll be working on meaningful projects to make an impact and deliver real value for our patients and our business.

Thesis Work Description:
The MolecularAI group at AstraZeneca uses start-of-the-art artificial intelligence (AI), machine learning algorithms, molecular simulation, and data science to develop models and tools that are used daily in drug discovery projects. We have developed several open-source platforms such as ReInvent for molecular design, AiZynthFinder for synthesis planning, and Maize for advanced simulation pipelines. We are now looking for students who will further develop our models and address their current limitations. Some projects will involve collaboration with experimental and computational chemistry departments of AstraZeneca. There are several projects that can be tailored to the student’s interest, including:
•    Evaluation of agentic AI architectures
•    AI methods in synthesis and reactivity prediction, covering ML, chemoinformatics, quantum chemistry in combination
•    AI methods in analytical chemistry science for reaction data analysis and structure elucidation
•    Flow matching models for molecules and conformers
•    Exploring novel deep learning architectures
•    Uncertainty and multi-objective optimization in reinceforcement learning
•    Combining machine learning with simulations in macro-molecular drug design
•    Ligand binding affinity prediction with machine-learned potentials
•    Investigating the effect of model bias in molecular property prediction
•    Molecular property prediction in low-data regime
•    Context-aware molecular property prediction
•    Multi-domain/multi-modal learning for molecular foundation models

Placement:
This is an on-site position at AstraZeneca Gothenburg
Please note, AstraZeneca does not support with accommodations for this role. 

Structure:
Duration: Spring 2027
Credits: 30

Essential Requirements:
·    Enrolled in a Swedish MSc program, or enrolled in the Erasmus Mundus Joint Master’s Degree ChEMoinformaticsPlus 
·    Knowledge in python programming, AI, machine learning, or algorithms. 
·    Studies in computer science, machine learning, AI, complex adaptive systems, cheminformatics, or similar. 
·    Chemistry / chemoinformatics background is a desired feature for some projects

Please state which project(s) you are interested in in your CV or cover letter and in the questionnaire.
If your program requires a paired thesis, please also include your thesis partner’s name in both CV/Cover letter and questionnaire.

So, what’s next?
Apply today and take the chance to be part of making a difference, making connections, and gaining the tools and experience to open doors and fulfil your potential. We can´t wait to hear from you!
We welcome your application as soon as possible, but ahead of the scheduled closing date October 04, 2026. In the event that we identify suitable candidates ahead of the scheduled closing date, we reserve the right to withdraw the vacancy earlier than published.

Date Posted

Closing Date