Thesis Work, 15 Credits - Analysis of Process Batch Data to Identify Lead Time Improvement Opportunities in Active Pharmaceutical Ingredient (Chemical) Manufacturing

Would you like to use data analytics to understand what affects lead times in pharmaceutical manufacturing? In this thesis project, you will analyze large volumes of batch data to identify bottlenecks and process variation, and develop insights to support production improvements. About AstraZeneca: AstraZeneca is a global, science-led, patient-centered biopharmaceutical company focusing on discovering, developing, and commercializing 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: A new control system has been introduced in production, and batch lead times are reported to be longer than with the previous system. In this thesis project, you will analyse batch execution data collected by the DeltaV process control system to investigate where delays and waiting times occur, what may be causing them, and where there is potential to improve overall lead times. You will develop a repeatable method for extracting, processing and analysing the available data, using Python or similar tools. The data may include information on process execution, equipment utilisation, waiting times, alarms, operator interventions and batch durations. Working with process engineers, operators and the automation team, you will validate your findings and assess which improvement opportunities could have the greatest impact.

. 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 20-okt.-2026

10-nov.-2026 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.