AstraZenecaThesis Work, 30/60 Credits - Confluency Atlas: Predicting Cell Growth and Cellular State Using AI
AstraZeneca is hiring a Thesis Work, 30/60 Credits - Confluency Atlas: Predicting Cell Growth and Cellular State Using AI in Gothenburg, Sweden. Level rates it ; you can apply on Level.
AI in this role
Conduct a Master's thesis project at AstraZeneca applying machine learning and cell biology to predict cell growth dynamics and cellular states.
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
12-okt.-2026Closing Date
02-nov.-2026Our 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.How we rate this
Thesis Work, 30/60 Credits - Confluency Atlas: Predicting Cell Growth and Cellular State Using AI at AstraZeneca rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
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- Tell me about a project where cell biology was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Cell Biology, Machine learning, and Data Analysis. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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