Chemical Engineer (PhD Position - Molecular Simulation and Machine Learning) | Chemieingenieur (m/w/d)

Job Summary

This PhD position, embedded within the Helmholtz Graduate School for Data Science in Life, Earth and Energy (HDS-LEE) at Forschungszentrum Jülich, focuses on developing predictive chromatography modeling using advanced data science techniques. The successful candidate will combine protein structure descriptors, molecular simulations, and machine learning to predict ion-exchange isotherm parameters directly from molecular properties. Day-to-day tasks involve developing molecular descriptors, designing and training QSPR and machine learning models, and integrating these predictions into the open-source CADET simulation framework for fully predictive process simulations. This interdisciplinary role sits at the intersection of bioengineering, computational biophysics, and data-driven modeling, offering strong links to open-source software development and industrially relevant bioprocess applications, making it an attractive opportunity for aspiring data scientists in the bioeconomy field.