PhD in Data Analytics

We are offering a three-year PhD fellowship in Biophotonics for Drug Delivery and Predictive Modelling commencing on 1st of April 2026 or as soon as possible thereafter./nProject description:/nRecent advances in ultra-narrow optical filtering, wavelength-stabilized lasers, and high-throughput spectrometers have made Brillouin and low-frequency Raman (LFR) spectroscopy practical, lab-friendly probes of nanoscale order and mechanics, which are critical determinants of formulation stability and drug-release performance. This project will leverage those tools to map structure-property relationships in polymeric drug delivery matrices, with particular emphasis on how semi-crystalline lamellae and amorphous domains coexist, compete, and evolve under processing and during hydration./nThe successful applicant will investigate how the fundamental structural, mechanical, and dynamic properties of semicrystalline and amorphous polymeric matrices determine the behavior of drug delivery platforms and model formulations. Spatial Brillouin microscopy will probe local elastic and viscoelastic responses, and low-frequency Raman spectroscopy will quantify lamellar and amorphous-domain vibrational signatures. Together, these measurements will establish mechanistic links between microscopic order, molecular mobility, and macroscopic performance metrics such as stability, dissolution, and release kinetics./nA central task will be the comparison of subcutaneous implants and oral tablets, used as model drug delivery systems. The applicant will examine how controlled thermal histories, hydration conditions, and drug-polymer co-assembly influence lamellar distributions, amorphous mobility, poroelastic water uptake, and balance between diffusion- and erosion-controlled release./nComplementary techniques, such as calorimetry, X-ray diffraction and small angle X-ray scattering, swelling studies, and in vitro release testing will be integrated with spectroscopic data using chemometrics, deep learning approaches (with an emphasis on one-dimensional convolutional neural networks) and data fusion models to generate predictive structure-performance relationships. The applicant will work closely with a Postdoc developing machine learning toolkits tailored for Brillouin and low-frequency Raman analysis and will be embedded in a research team consisting of an Assistant Professor, two Postdocs, and three PhD students./nPlace of employment: Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.