Thesis work, 30 credits - High-content Imaging & AI-enabled Analysis for Drug Discovery

Are you passionate about combining cutting-edge microscopy, AI, and drug discovery? Do you have experience or interest in working with advanced robotic confocal microscopes? Want to learn more about high-content imaging and AI-enabled image analysis? 

Then this master thesis opportunity is perfect for you! 

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 Team and Business Area: 

You will join the Biosciences Technology Imaging Team within AstraZeneca’s Cardiovascular, Renal, and Metabolism (CVRM) area. Our team plays a pivotal role in leveraging state-of-the-art imaging technologies to generate and analyse data from complex biological systems. We collaborate across departments to deliver deep insights from compound screening and mechanistic studies, supporting innovative drug discovery programs. 

Thesis Summary: 

This Master’s thesis aims to advance drug discovery by integrating high-content confocal imaging with AI-assisted analysis. As part of AstraZeneca’s Biosciences Technology Imaging Team, you will develop and optimize cutting-edge image-based assays in collaboration with world-class scientists. By leveraging the latest in hardware (Cell Discoverer 7) and software (ARIVIS Pro-AI), your work will help extract actionable biological insights from complex cellular systems, contributing directly to novel therapeutic development in the Cardiovascular, Renal, and Metabolism (CVRM) field. 

Thesis Work Objectives:  

Establish and Optimize High-Content Imaging Assays 

• Develop robust in vitro and ex vivo imaging assays using the Cell Discoverer 7 platform. 
• Trouble-shoot protocols and ensure high-quality, reproducible image data. 

Implement AI-Enabled Image Analysis 

• Utilize ARIVIS Pro-AI for automated feature recognition and quantification in large-scale image datasets. 
• Compare AI-enabled results to conventional analysis methods for improved assay robustness. 

Generate and Interpret Quantitative Biological Data 

• Extract phenotypic and mechanistic insights from imaging data to support CVRM drug discovery projects. 
• Present findings in clear reports and presentations for internal stakeholders. 

Collaborate Effectively within Cross-Functional Teams 

• Work closely with bioscientists, data scientists, and automation engineers to ensure seamless integration of imaging and analysis workflows. 

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.  

Structure:  

• 30 credits 
• Start date: Flexible 
• Location: Gothenburg 

Essential Requirements: 

• Ongoing master’s studies within Pharmacy, Engineering, or equivalent. 
• Well-organized and focused mindset 
• Strong oral and written communication skills. 
• Experince in python conding 

Desirable Requirements: 

• Enthusiasm for learning and experimenting with new technologies and methodologies. 

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 30th of June 2025. 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.