PhD/Postdoc Position for Safe Machine Learning for Power Systems

28.07.2021, Wissenschaftliches Personal

The research group Cyber-Physical Systems of Prof. Matthias Althoff at the Technical University of Munich offers a PhD/Postdoc position in the area of safe machine learning for power systems. The Technical University of Munich is one of the top research universities in Europe fostering a strong entrepreneurial spirit and international culture.

Expected Starting Date: 01 October 2021-01 February 2022

Closing Date for Applicants: 30 September 2021

Duration: 3 years with a possible extension (individual duration for Postdocs).

Project and Job Description

To cope with the challenges of a sustainable energy supply, machine learning is increasingly deployed in power systems. Often, learned controllers are encoded in the form of neural networks, which are very difficult to analyze and verify. Machine learning will play an increasing role in power systems, whose correct behavior has to be a top priority. However, current solutions do not provide any correctness guarantees. Thus, one of the main objective of this position is to safeguard methods from machine learning in power systems using methods from formal verification. The research will build upon first results from safe machine learning for autonomous vehicles, see, e.g.,

. Our previous methods on verifying power systems (see

) should also be further developed and combined with novel machine learning methods, in particular reinforcement learning. Results should be demonstrated in the Center for Combined Smart Energy Systems (CoSES) at the Technical University of Munich. CoSES is not only a research facility, but also an open, interdisciplinary research group covering expertise from several chairs and departments, ranging from energy management to communication technology. In particular, we will investigates microgrids that combine electrical as well as thermal energy systems.

Job Specifications

• For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics).
  
• For Postdoc applicants: Excellent track record in computer science or engineering.
  
• Fluency in spoken and written English is required.
  
• Good programming skills in at least one programming language, e.g. MATLAB, C/C++, Python.
  
• Highly motivated and keen on working in an international and interdisciplinary team
  
• Applicants with strong background in the following fields are preferred:
  
• Machine learning
  
• Formal verification
  
• Control theory
  
• Power systems

Context

The applicant will be directly advised by Prof. Matthias Althoff (

). Besides excellent skills for conducting innovative science, the candidate should also be talented in implementing research results on real systems and lead teams of students. Our Offer PhD remuneration will be in line with the current German collective pay agreement TV-L E13 (around 4300 Euros/month). Technical University of Munich is an equal opportunity employer committed to excellence through diversity. We explicitly encourage women to apply and preference will be given to disabled applicants with equivalent qualifications.

Contact

International candidates are highly encouraged to apply. Please send a complete application (in English or German) including a CV, your Master’s thesis (only for PhD applicants), your full transcript of records (only for PhD applicants) and contact details to Mrs. Xiao Wang ([email protected]). Please do not include a cover letter. We kindly ask you to use the subject line “Application to Safe Machine Learning for Power Systems” in your application email. Further similar job offerings will be announced on https://www.in.tum.de/en/i06/open-positions/scientific-staff/.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: Mrs. Xiao Wang ([email protected])