PhD position in Reinforcement Learning for Chemistry
Department of Computer Science
Institute of Theoretical Informatics
Do you have experience in machine learning and reinforcement learning? Are you motivated to do a PhD in an interdisciplinary setting and join an ambitious young research group to work on an exicting PhD topic at the interface of computer science and chemistry?
Yes? Then apply now for a PhD position in the AiMat research group at KIT!
- You will work on the development of reinforcement learning algorithms based on graph neural networks for the design of molecules and materials
- You will be able to participate in a research projected funded by the Federal Ministry for Economic Affairs and Energy and collaborate with an industry partner with expertise in organic electronics
- You will be able to participate in teaching activities on the Bachelor's and Master's level in computer science (German or English)
- You will have the opportunity to present your research on international conferences and publish in international research journals
What we offer
- Highly interdisciplinary and international team of students and postdocs
- Exciting research topics, state-of-the-art machine learning methods, applied to highly relevant challenges in materials science and chemistry
- Great national and international collaboration partners in academia and industry
- Fully funded PhD position (TV-L E13)
What we are looking for
- Highly motivated young researchers (male/female/diverse)
- Background and experience in computer science, machine learning and reinforcement learning
- Interest to learn more about exciting application areas of machine learning in chemistry
- Creativity, independence, teamwork and communication skills, motivation to make a change and have an impact in research
- As soon as possible
- Fully funded position (100%), according to TV-L E13.
- Up to 3 years
Contact and information
Please send your application including cover letter, CV, contact information for references or reference letters as well as copies of degrees and certificates to
- T.T.-Prof. Dr. Pascal Friederich, firstname.lastname@example.org
We prefer to balance the number of female and male employees. Therefore, we kindly encourage female applicants to apply for this job.
Recognized severely disabled persons will be preferred if they are equally qualified.