Graduate Researcher (m/f/d) in Materials Informatics

The Kuenneth Group at the University of Bayreuth is dedicated to democratizing machine learning in materials science. Such materials informatics efforts are underway more vigorously than ever before to streamline materials design, discovery, development, and deployment efficiently and effectively. To contribute to this exciting field, the Kuenneth group primarily concentrates on two research directions: (i) innovative machine learning techniques in materials science, and (ii) utilizing these techniques to study a diverse range of materials. The special focus of the Kuenneth group is sustainable and polymeric materials.

What you will do

• Developing and integrating machine learning models in the field of materials science and engineering
• Strategies for materials space explorations and inverse design
• Large language models for materials science
• Data extraction, curation, and organization
• Independent research

What you bring to the table

• Above average master's degree in engineering, natural sciences, computer science or related fields
• Strong programming skills in Python
• Curiosity towards scientific topics related to materials and data science
• Motivation and proactivity, along with independence, creativity, and communication skills in English and German

What you can expect

• Possibility to pursue a doctoral degree (PhD position, TV-L E13)
• Flexibility in working hours with the option to work from home
• Engaging in innovative and data-driven scientific research alongside application-oriented projects
• Access to a wide range of industrial and international contacts
• Pleasant working atmosphere and social events

Your research is carried out at the Computational Materials Sciences Group (Kuenneth group) at the University of Bayreuth. This position comes with a salary of 80% of the E13 level.

The University of Bayreuth appreciates the diversity of its employees as an enrichment and is expressly committed to the goal of equal gender opportunities. Women are strongly encouraged to apply. Applicants with children are very welcome. The University of Bayreuth is a member of the Best Practice Club "Familie in der Hochschule e.V." and has successfully participated in the HRK audit "Internationalization of the University". People with severe disabilities will be given preferential consideration if they have the same aptitude.

Please apply online with meaningful application documents using the password "MI2025_1" via the application portal of the University of Bayreuth. The documents will be deleted after the position has been filled in accordance with data protection requirements.

For further inquiries please contact: Prof. Dr. Christopher Künneth (apply.mi@uni-bayreuth.de)