About the institute: As a member of the Leibniz Association, the Leibniz Institute of Plant Biochemistry (IPB) is a non-university research institution on the Weinberg Campus in Halle (Saale). As a foundation under public law, the IPB is under the supervision of the state of Saxony-Anhalt, Germany. The IPB is an internationally renowned research institution and consists of four scientific departments and additional independent research groups (approx. 200 employees, including around 40 doctoral students). Research at the IPB aims to understand the (bio)chemical basis of the performance and resilience of plants under environmental conditions of climate change. The IPB offers excellent research conditions and a state-of-the-art infrastructure to investigate the chemical diversity, biochemical interactions and biological functions of small natural product molecules in plants and fungi. The focus is on specialized metabolites, chemical mediators and relevant molecular networks of functional gene and protein regulation ( http://www.ipb-halle.de ). At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD candidate in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part-time 65 %, limited for 3 years, start: as soon as possible) Are you passionate about machine learning, molecular science, and making discoveries at the interface of biology and chemistry? Join us at the Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the Project & Group: You will work in the Computational Chemistry group, led by Dr. Mehdi D. Davari, an interdisciplinary team focused on accelerating chemical and biological discovery using computational tools. Our research combines computational chemistry, cheminformatics, bioinformatic and AI to design new molecules and enzymes for unprecedented catalytic functions. In this project, you will: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools. Collaborate closely with an experimental enzymology PhD student to validate your models in the lab. This is an excellent opportunity to contribute to the future of enzyme engineering, bioinformatics, and molecular ML in an exciting, interdisciplinary environment. For more information about our group and research topics, visit: IPB Halle Department of Bioorganic Chemistry (NWC) Who We're Looking For: We’re seeking a creative, motivated, and collaborative candidate with the following qualifications: Essential: Master’s or Diploma degree in Bioinformatics, Computational (Bio)Chemistry, Cheminformatics, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability to communicate ideas and results effectively Independent and solution-oriented work ethic Interdisciplinary mindset and enthusiasm for teamwork Ability to work in a multi-cultural, multi-ethnic environment with sensitivity and respect for diversity Desirable: Experience in cheminformatics, molecular modeling, or enzyme mechanisms Familiarity with databases, data mining, and knowledge management Why Join Us: Be part of a dynamic, growing team in the field of enzyme and protein design Collaborate in the context of a prestigious DFG Priority Programme (SPP2363) Enjoy a vibrant scientific environment at the Weinberg Campus, Halle, co-located with the Martin Luther University Work in a highly international, supportive, and diverse research atmosphere Access to cutting-edge facilities in biotechnology, structural biology, proteomics, metabolomics, and more Our benefits: Excellent working conditions in an international environment Flexible and family-friendly working hours and possibility of home-office Offer of professional training courses and measures for skill improvement Compensation according to TV-L (including annual special payment) Contribution to your company pension plan (VBL) On-site opportunities for health promotion