Job Description

Are you curious about the science behind nanosuspensions and passionate about improving analytical workflows in drug development? We are seeking a motivated master’s thesis student to investigate why early-stage nanosuspensions sometimes yield drug concentrations higher than theoretically predicted, and to help develop predictive and control strategies. Join our team and contribute to making pharmaceutical analytical data more reliable and formulation processes more robust!

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, you will find an environment that is 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:

In some early-stage nanosuspension formulations, measured drug concentrations are observed to exceed the theoretical values calculated from weighed inputs—an effect known as “apparent over-recovery.” This phenomenon complicates data interpretation, analytical method qualification, and decision-making during compound progression. The aim of this thesis is to identify the root causes of over-recovery, establish criteria for compounds and conditions at risk, and propose practical strategies for prediction, prevention, and control.

You will explore possible contributing factors such as assay bias, sampling and dilution artifacts, particle-size–dependent detection, solid-state transformations, surface adsorption/desorption effects, and process variability through a combination of experimental studies and analytical cross-validation. Insights from your work will feed into the development of a decision framework to enable early risk prediction—using physicochemical descriptors and process parameters—and to guide formulation or analytical adjustments when issues are detected.

By transforming the approach from reactive troubleshooting to predictive management, this thesis aims to streamline early formulation and analytical workflows, reduce rework, improve data reliability, and support faster development decisions for challenging compounds.

Key Objectives:

• Investigate and map the possible causes of “apparent over-recovery” in early-stage nanosuspensions through systematic experimental and analytical studies.
• Evaluate the impact of assay bias, sampling and dilution errors, particle size effects, physical transformations, surface adsorption/desorption, and process variability on concentration measurements.
• Develop criteria to identify compounds and nanosuspension conditions that are prone to over-recovery behavior.
• Propose robust strategies for analytical method and process control to prevent or minimize over-recovery.
• Create a decision framework for early risk prediction and practical guidance, incorporating physicochemical and process parameters.
• Contribute to continuous improvement of formulation and analytical workflows, promoting predictive and learning-based approaches over ad hoc troubleshooting.

Placement

This is an on-site position at AstraZeneca Gothenburg. AstraZeneca does not support with accommodations for this role.

Structure
• Duration: Start fall term 2026
• Credits: 30

Essential Requirements:

• Enrolled in a master’s program within physical/analytical chemistry, pharmaceutical sciences, or chemical engineering.
• Hands-on lab experience with routine analytical techniques (e.g., HPLC/UPLC, UV–Vis, DLS/laser diffraction; basic solid-state methods preferred). Experience with colloids/nanosuspensions is a plus.
• Familiarity with method development/qualification, dilution and sampling best practices, and error/uncertainty analysis.
• Ability to execute experiments, document, and communicate findings clearly in writing and presentations.
• Proactive, hypothesis-driven mindset; comfortable collaborating with formulation and analytical teams.

• Excellent English communication skills, including speaking, presenting and scientific writing.

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 21st of April 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

31-Mar-2026

Closing Date

21-Apr-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.