Could AI help us predict not only how cells grow, but also how they behave? Join AstraZeneca to explore how cell growth dynamics may reveal deeper biological phenotypes, including cell cycle progression and cellular state. This thesis project combines cell biology, machine learning, FAIR data principles and digital laboratory innovation to support future experimental planning and AI-enabled assay development.

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 Confluency Atlas is an AI-driven platform that transforms time-series cell growth data into predictive models for cell seeding and culture optimization. This thesis will investigate whether patterns in cell growth can be linked to deeper biological phenotypes, including cell cycle progression and cellular state. The aim is to explore whether these dynamics can help predict not only how cells grow, but also how they behave.

The work will bring together cell biology and AI, applying FAIR data principles to support the effective use of experimental data. By connecting cell growth patterns with cellular phenotypes, the project will contribute to digital laboratory innovation and help inform future AI-enabled reagent and assay design, automation, acceleration and experimental planning across Discovery Sciences.

Placement:  

This is an on-site position at AstraZeneca Gothenburg.

AstraZeneca does not support with accommodations for this role

Structure:

• Duration: Start Spring 2027
• Credits: 30/60

Essential Requirements:

• Enrolled in a Master’s programme in cell biology or a related field.
• Good knowledge of cell biology.
• Interest in cell growth, cell culture and cellular phenotypes.
• Familiarity with AI models or machine-learning models is an advantage
• Experience with hands-on cell culture is a plus.
• Experience with programming, such as Python or R, is an advantage.
• Good communication skills in English.

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 November 02, 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