Leibniz-Institut für Pflanzenbiochemie
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PhD in Machine Learning for Enzyme Design Leibniz Institute of Plant Biochemistry in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Germany
University
Leibniz-Institut für Pflanzenbiochemie
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About this position
At the Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, a fully funded PhD position is available in the Department of Bioorganic Chemistry on Machine Learning for Enzyme Design. The project sits within the DFG Priority Programme SPP2363, Molecular Machine Learning, and is hosted by the Computational Chemistry group led by Dr. Mehdi D. Davari.
The PhD project is aimed at students interested in the interface of machine learning, computational chemistry, bioinformatics, cheminformatics, and enzyme engineering. The successful candidate will develop innovative machine learning architectures for the mining, prediction, and design of enzymes, using modern approaches such as deep learning and generative models alongside computational biochemistry tools. The work is interdisciplinary and collaborative, with close interaction with an experimental enzymology PhD student for laboratory validation of model predictions.
IPB is an internationally recognized non-university research institute on the Weinberg Campus in Halle, with strong expertise in plant biochemistry, chemical biology, and molecular networks. The institute emphasizes a highly international, supportive, and diverse research environment and provides access to advanced facilities in biotechnology, structural biology, proteomics, metabolomics, and related areas. The position is part-time (65%), paid according to TV-L E13, and limited to 3 years.
Applicants should hold a Master’s or Diploma degree in Bioinformatics, Computational (Bio)Chemistry, Cheminformatics, Computational Biophysics, or a closely related field. Strong programming skills, familiarity with machine learning frameworks such as PyTorch or TensorFlow, very good English, and an independent, solution-oriented, team-oriented working style are required. Experience in cheminformatics, molecular modeling, enzyme mechanisms, databases, data mining, or knowledge management is considered desirable. The institute also highlights equal opportunity, diversity, family friendliness, and welcomes applications from disabled persons or applicants with equivalent status.
Applications are reviewed immediately and accepted until the position is filled. To apply, submit a single PDF by email to the institute’s recruitment address, including a cover letter, CV, transcripts, and referee details or recommendation letters. Informal questions can be directed to Dr. Mehdi D. Davari.
Funding details
Available
What's required
Master’s or Diploma degree in Bioinformatics, Computational (Bio)Chemistry, Cheminformatics, Computational Biophysics, or a closely related field; strong programming skills in Python and/or C/C++; knowledge of machine learning frameworks such as PyTorch or TensorFlow; very good English language skills; independent and solution-oriented working style; interdisciplinary mindset and enthusiasm for teamwork; ability to work in a multi-cultural, multi-ethnic environment with sensitivity and respect for diversity. Desirable experience includes cheminformatics, molecular modeling, enzyme mechanisms, databases, data mining, and knowledge management. Foreign qualifications must meet German standards and be certified/equivalence-tested in Germany.
How to apply
Email a single PDF application to [email protected] with the subject line 'PhD ML Enzyme Design – Ref No. 11/2025'. Include a cover letter, CV with publication list if applicable, academic transcripts, and contact details of two academic referees or two recommendation letters. Applications are reviewed immediately and accepted until the position is filled.
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Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.