Research Associate / Wissenschaftliche*r Mitarbeiter*in at the Institute of at Technische Universitt Hamburg
21073 Hamburg, , Germany -
Full Time


Start Date

Immediate

Expiry Date

28 Sep, 25

Salary

0.0

Posted On

16 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Control Engineering, Process Engineering, Cybernetics, Uncertainty Quantification, Machine Learning, Process Control

Industry

Electrical/Electronic Manufacturing

Description

Research Associate
(m/f/d) /
Wissenschaftlicher Mitarbeiterin (m/w/d)
Institute Institute of Control Systems RemunerationEG 13
TV-L
ID: 23425WE14
Start of employment January 1st 2026
Application deadline August 29th 2025
Scope full time and limited until June 30th 2027 The Institute of Control Systems conduct method oriented and basic research on the system-theoretic analysis and control of non-linear and cyber-physical systems subject to epistemic and aleatoric uncertainty. The span of considered application entails multi-energy systems and networks, mechatronic and robotic systems and process systems. Our research is embedded in a productive network of international and national collaborations.
The institute is looking for a scientific staff member to support its research in the Collaborative Research Center 1615 "
SMART Reactors
“. Candidates preferably have a strong background in modern process systems engineering and process control. In particular, we are looking for candidates with strong expertise in data-driven methods, or machine learning, or artificial intelligence for process control. Knowledge of optimization-based and predictive control is a plus. Also knowledge of kernel-methods in machine learning or of uncertainty quantification techniques is considered a plus.

NOTICE FOR GRADUATES OF FOREIGN EDUCATIONAL QUALIFICATIONS:

Please submit proof of all obtained university degrees and, if available, the recognition of your educational qualifications in Germany (e.g. anabin excerpts and/or acknowledgement of previous employers).
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Responsibilities
  • Research on data-driven control of nonlinear process systems
  • Support of the institute in teaching and research
  • Involvement in national and international research collaborations
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