Postdoctoral Researcher in the Research Group Applied Computer Science for Energy Systems

Job description

The newly established research group Applied Computer Science for Energy Systems at the AIFB Institute deals with using data for enhancing energy efficiency of cyber-physical systems, as well as decision support for energy systems. In particular, our focus is on the development of new methods and approaches for data-driven modeling and simulation.

Your activities will include research in the field of data-driven modeling and simulation for enhancement of energy efficiency and energy systems. In addition to research work, you will be also active in coordination and teaching of courses that are offered by the research group, and you will be involved in science administration.

Personal qualification
  • A doctoral degree in computer science, software engineering, data science or similar,
  • Solid publication record in data-driven approaches,
  • Good knowledge of German or the willingness to learn it
  • Good command of English,
  • Strong ambition towards excellence in science and technology at the highest international level is expected,
  • Experience with writing proposals is highly appreciated,
  • Experience in modeling and simulation is highly appreciated.
Salary

The remuneration occurs on the basis of the wage agreement of the civil service in EG-13, depending on the fulfillment of professional and personal requirements.

 we offer

Organizational unit

Institute of Applied Informatics and Formal Description Methods (AIFB)

Starting date

15. Oktober 2022

Contract duration

limited for 2 years with the possibility of extension

Application up to

September 15, 2022

Contact person in line-management

For further information, please contact Prof. Sanja Lazarova-Molnar, email: sanja.lazarova-molnar@kit.edu.

Application

To apply for the position, please submit your application via e-mail addresses: sanja.lazarova-molnar@kit.edu given as one single PDF document, which should include letter of motivation (no more than one page), CV (indicating your contact information, work history, list of publications, knowledge areas of computer science, experimental skills, language skills, university degrees and grades, honors and awards), and two letters of recommendation or contact details of two possible referees.

 

vacancy number: 2174/2022

 

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.