PhD Position in Cheminformatics and Machine Learning

SDU Life Cycle Engineering at the Department of Green Technology , University of Southern Denmark, invites applications for a PhD position in cheminformatics and machine learning. The position will contribute to PFAROS, a flagship European research project dedicated to driving sustainable innovation and supporting the transition toward PFAS-free healthcare in Europe. Working at the intersection of chemistry, environmental science, artificial intelligence, and data science, the successful candidate will help advance next-generation approaches for chemical assessment by integrating diverse data streams, developing cutting-edge predictive models, and generating knowledge that supports safer and more sustainable chemical and material innovation. Through collaboration with leading international researchers and stakeholders, the position offers a unique opportunity to contribute to high-impact science addressing some of society’s most pressing environmental and health challenges. The position will contribute to ongoing research projects and activities at SDU Life Cycle Engineering. Main tasks The main tasks include: Collect, curate, and validate high-quality physicochemical, environmental, and hazard property data for chemicals in commerce. Evaluate and document the applicability domains and coverage of existing machine learning models used for predicting chemical properties. Develop, train, validate, and benchmark new models for chemical property prediction, including machine learning and generative AI-based approaches. Contribute to the integration of experimental data, computational methods, and machine learning workflows. Participate in collaborative research activities within the PFAROS consortium and interact with international project partners. Contribute to scientific publications, conference presentations, reports, and the development of new research proposals. Qualifications The successful candidate should have: MSc degree (or equivalent) in chemistry, environmental science, chemical engineering, computer science, data science, bioinformatics, or a related field. Strong interest in machine learning, cheminformatics, data science, and chemical risk assessment. Experience with programming in Python and scientific computing. Familiarity with machine learning methods, data management, and statistical analysis. Experience with chemical databases, molecular descriptors, QSAR models, or cheminformatics tools is an advantage. Excellent written and oral...

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