Thesis Work, 30/60 Credits - Confluency Atlas: Predicting Cell Growth and Cellular State Using AI

AstraZeneca; Göteborgs kommun; On-site; SEK 167,000 - 212,000; Full time

Job summary

AstraZeneca invites a Master’s student to join as a Thesis Worker in Gothenburg, focusing on AI-driven analysis of cell growth to infer phenotypes and optimize experimental planning. The project blends cell biology with machine learning under FAIR data principles to support future assay development and digital laboratory innovation.

The placement is on-site at AstraZeneca Gothenburg, offering meaningful, real-world research opportunities and collaboration with Discovery Sciences teams.

Qualifications

• Enrolled in a Master’s programme in cell biology or 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.

Responsibilities

• Work on the Confluency Atlas AI-driven platform transforming time-series cell growth data into predictive models.
• Investigate links between growth patterns and biological phenotypes such as cell cycle progression and cellular state.
• Apply FAIR data principles to enable effective use of experimental data for AI-enabled reagent and assay design and planning.
• Collaborate with Discovery Sciences to inform experimental planning and digital laboratory innovation.

Skills

Cell biology

Python

R

English communication

AI / machine learning

Education

Master’s degree in cell biology

Tools

Python

R

Job description

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.

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.