Research Associate (f/m/d) for Reinforcement Learning in Materials Science

together unique

Institute for Applied Materials - Microstructure-Modeling and Simulation (IAM-MMS), Institute of Nanotechnology (INT)

Your task involves the development of reinforcement and active learning methods for materials science problems with data-integrative approaches. To this end, you create workflows in the ecosystem of the data platform Kadi4Mat and extend them with nodes for machine learning.

Further tasks include the implementation of machine learning methods and contributing to the development of the software solutions CIDS, KadiAI, and Kadi.

The results of the work will be shared within the institute, presented at conferences, and published in scientific journals.

It is possible to pursue a doctorate as part of your career.

zum nächstmöglichen Zeitpunkt / as soon as possible

Completed university degree or doctorate in a mathematical, engineering, natural science, or data science discipline.

Experience in machine learning (especially deep and reinforcement learning) and programming skills in Python (especially PyTorch or TensorFlow) are mandatory.

Salary category EG 13, depending on the fulfillment of professional and personal requirements.

limited to 1 year

March 15, 2023

For further information, please contact Dr.-Ing. Koeppe, email: [email protected]

Please send your application including a cover letter, your CV, and all certificates/referees in electronic form to: [email protected]

vacancy number: 2065/2023

We prefer to balance the number of employees (f/m/d). Therefore, we kindly ask female applicants to apply for this job.

Recognized severely disabled persons will be preferred if they are equally qualified.