Research Associate (m/f/d) in the field of Multiscale Simulation of Electrochemical Flow Reactors with Machine Learning

The research group for Methods of Battery Management (www.mbm.uni-bayreuth.de/en/) at the Bavarian Centre for Battery Technology (BayBatt, www.baybatt.uni-bayreuth.de/en/) at the University of Bayreuth has an open fixed-term (full-time) position as a

Electrochemical flow reactors are a key enabling technology for the electrification of the chemical industry and the storage of renewable energy. Tailored design and operation require sophisticated models that consider processes across scales. Our goal is the development of advanced multiscale modeling techniques for the simulation of electrochemical flow reactors by expoiting novel machine learning techniques. The project is part of the priority program Machine Learning in Chemical Engineering (SPP 2331) funded by the German research association DFG.

Tasks:

• Exploiting advanced machine learning methods for multiscale simulations
• Development of novel numerical methods
• Performing multiscale simulations of electrochemical flow reactors

Qualifications:

• Completed university degree (Master's or Diploma) in Engineering, Applied Math, Physics, Scientific Computing or related fields
• Strong background in numerical simulations at continuum or atomistic scale
• Keen to use sophisticated machine learning methods
• Communication skills and a researcher mindset

Scientific Environment:

As a PhD candidate or Post Doctoral researcher, 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.

If you are interested in this exciting research opportunity, please submit your application documents, including cover letter, CV, transcript of records and references, online via our application portal at the University of Bayreuth.

Application deadline is  31.12.2024    Code: ChemAI

The documents will be deleted in accordance with data protection regulations as soon as the position is filled.

If you have any questions, please contact: Prof. Dr.-Ing. Fridolin Röder, Professor for Methods of Battery Management, fridolin.roeder@uni-bayreuth.de, Tel.: +49 (0)921 / 55-4940.