Researcher (Ph.d. or Early Post-Doc Phase): Learning Control Algorithms for Electrical Systems
DE, 57076
Applications have closed
Universität Siegen
Area: Faculty IV: School of Science and Technology | Job scope: full-time | Duration of employment: limited | Posting-ID: 6331
The University of Siegen is a modern university with an international orientation and a focus on interdisciplinary research. It currently has around 15,000 students and covers a range of research fields from the humanities, social and economic sciences to natural sciences, engineering and life sciences. With over 2,000 employees, the university is one of the largest employers in the region and offers a unique environment for teaching, study, research and knowledge transfer.
We seek:
- In the Faculty IV: School of Science and Technology, Chair of Interconnected Automation Systems, we are looking for a researcher as of the next possible date at the following conditions:
- 100% = 39,83 hours
- Pay grade 13 TV-L
- limited for three years
Your tasks:
- Research on optimal control methods for intelligent technical systems (with a focus on electrical energy systems)
- Combination of adaptive machine learning methods and interpretable expert-driven control approaches
- Transfer of theoretical control concepts from simulation-based pre-investigations to real-world experiments
- Publication of research results in relevant international journals and conference proceedings
- Scientific exchange and active cooperation with related research groups
- Contributing to open-source software and data repositories addressing the above topics
- Teaching support (e.g., hosting exercise sessions, project groups or student theses)
Your profile:
- Very good university degree (master, Ph.D. or similar) in the field of control engineering, electrical engineering, mechatronics, computer science or similar
- Profound knowledge of optimal control of dynamic systems using model-based and/or model-free approaches (model predictive control, reinforcement learning, differential predictive control,...)
- Profound knowledge of software-related engineering tools and programming languages (e.g., Python, JAX, Julia, Matlab/Simulink, VHDL, C/C++,...)
- Desirable: practical experience in working at laboratory test benches for embedded systems (using microprocessors, FPGAs or rapid-control-prototyping systems)
- Willingness to engage in interdisciplinary research cooperation
- Ability to work independently as well as part of a team
- Very good command of written and spoken English
Our range of services:
- Promotion of own scientific qualification according to the Wissenschaftszeitvertragsgesetz [act on temporary employment in higher education] (e.g., doctorate degree or early post-doc qualification)
- Diverse opportunities to take on responsibility and make a visible contribution in the research and teaching environment
- A modern understanding of leadership and collaboration
- Good work-life balance, for example, through flexible working hours and work location, as well as support with child care
- Extensive personnel development program
- Health management with a wide range of prevention and counseling services
We look forward to receiving your application by 2024-09-22.
Please apply exclusively via our job portal (https://jobs.uni-siegen.de). Unfortunately, we cannot consider applications in writing or by e-mail.
Your contact person:
Prof. Dr.-Ing. Oliver Wallscheid
0271 / 740 3357
oliver.wallscheid@uni-siegen.de
Equal opportunities and diversity are promoted and embodied at the University of Siegen. The advertisement is explicitly addressed to people of all genders; applications from women will be given special consideration in accordance with the State Equal Opportunities Act. We also welcome applications from people with different personal, social, and cultural backgrounds, people with severe disabilities, and people of equal status.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Engineering JAX Julia Machine Learning Matlab Open Source Prototyping Python Reinforcement Learning Research Teaching
Perks/benefits: Career development Flex hours
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