Fixed-Term Research Associate (m/f/d) in the field of Autoregressive Machine Learning for Electrochemical Interfaces

The University of Bayreuth is a research-oriented university with internationally competitive, interdisciplinary focus areas in research and teaching. The Chair of Physical Chemistry V: Theory and Machine Learning (www.margraf.uni-bayreuth.de) located at the University of Bayreuth’s Bavarian Center for Battery Technology (BayBatt) is currently seeking to appoint a

to commence as soon as possible.

Tasks:

• Develop novel autoregressive ML methods to describe the time-evolution of electrochemical interfaces
• Collaborate on integrating ML models into multiscale simulations of electrochemical flow reactors
• Develop novel methods for representation learning of chemical reaction networks

Qualifications:

• Completed university degree (Master's or Diploma) in Chemistry, Physics, Computer Science or related fields
• Strong background in numerical simulations at the atomistic scale and/or modern ML techniques
• Interest in pushing the boundaries of multiscale simulations
• Strong communication skills and a curious mind

Scientific Environment:

As a PhD candidate, you will have access to modern research facilities at the Bavarian Center of Battery Technology and a supportive research environment. You will also have the opportunity to collaborate with leading experts in the field and participate in international conferences and workshops.

The University of Bayreuth, with its family-friendly campus, is one of the largest employers in the region. The University of Bayreuth values the diversity of its employees as an enrichment and is expressly committed to the goal of equal opportunities for men and women. Women are expressly encouraged to apply. Applicants with children are 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 ‘Internationalisation of the University’. Persons with severe disabilities will be given preferential consideration if equally qualified.

Please apply online with detailed application documents by 31.12.2024 using the application portal of the University of Bayreuth, stating the password “ML4Echem”. Application documents will be deleted in accordance with data protection law following the conclusion of the appointment process.

 If you have any questions, please contact: Prof. Johannes Margraf, johannes.margraf@uni-bayreuth.de