Thesis Work, 30 Credits - NIR and Raman Spectroscopy in Pharma Manufacturing

About the role

AstraZeneca is offering a 30-credit thesis placement in Gothenburg, Sweden, for students who want to apply spectroscopy, chemometrics and process modelling to real-time pharmaceutical manufacturing. The project investigates whether NIR and Raman spectroscopy can independently predict all active pharmaceutical ingredients and excipients in a formulation during continuous direct compression. It is an on-site position in the spring of 2027.

Key responsibilities

• Investigate whether NIR and/or Raman spectroscopy can predict every API and excipient in a formulation in real time, and assess whether each component is independently identifiable.
• Compare single-component PLS models (PLS1) with multicomponent models (PLS2).
• Study physically constrained models such as non-negative concentration predictions, formulation mass balance and mechanistic models.
• Explore hybrid models that combine spectroscopy with process information.
• Design calibration mixtures to separate true spectral information from chance correlations.
• If possible, test selected approaches dynamically on a continuous direct compression platform.
• Work closely with scientists experienced in PAT, spectroscopy, pharmaceutical processing and data analysis.

Required profile

• Enrolled in a Master's programme in analytical chemistry, pharmaceutical science or technology, chemical engineering, engineering physics, applied physics, applied mathematics, chemometrics, data science or a related discipline.
• Fundamental understanding of spectroscopy and its underlying chemical and physical phenomena.
• Strong interest in multivariate modelling, process modelling, data analysis, automation and experimental design.
• Laboratory experience is desirable.
• Excellent English, including scientific writing and presentations.

Required skills

• Experience with Python and/or MATLAB is highly desirable.