The research topics at the intersection of mathematical systems theory and data-based methods with application to the distribution grid include, among others, the following ones:

• Energy dispatch management with uncertainty propagation and quantification (e.g., uncertain forecasts) in DC systems.
• Model- and data-based methods for predictive dispatch optimization and control
• Optimization under uncertainty as a basis for robust fault-tolerant control and operation management
• analysis and data-driven control design taking dynamic, time-varying cross-sector flexibilities into account 

In a interdisciplinary team (the ThEFI unites 13 disciplines from 4 faculties) novel methods in the mentioned topic area shall be developed and scientifically investigated. ThEFI offers the necessary laboratory infrastructure in its Technological Center.

Your tasks

The position includes the following responsibilities:

• Design, implementation, and analysis of model- as well as data-based predictive control schemes
• Design and analysis of operation management and control concepts in physics-informed data-driven manner for optimal deployment of potentially decentralized energy conversion systems
• Modeling of cross-sectoral flexibilities and uncertainties and their integration in the control, e.g., uncertainty propagation
• application of the developed methods for representative energy systems
  
• Publication of project results in international top-tier journals as well as writing reports for the project

Your profile

For being part of the selection process is needed:

• Excellent degree (master, university diploma or equivalent) in mathematics or a related field; a PhD in applied mathematics is appreciated, but not mandatory
• Application experience of system-theoretic methods; preferably related to energy systems
• Very good knowledge of mathematical systems theory, qualitative theory of differential equations, and functional (e.g., kernel-reproducing Hilbert spaces and similar concepts important in the mathematical analysis of machine learning techniques)
• Knowledge of data-driven modeling and control of dynamical systems
• programming skills, ideally Python and MatLab/Octave

Following competences are desirable:

• Commitment, enthusiasm, independent working style, initiative and ability to work in a team
• Very good communication skills in German and English

Please provide evidence of the qualifications required for the job by certificates and references.

What we offer you:

• Attractive remuneration according to collective agreement (as per TV-L) incl. granting of a special annual payment
  
• Vacation entitlement of 30 days in the calendar year and additional days off on 24 / 31 December.
• Flexible working time model and overtime compensation
  
• VBL - pension scheme in the public sector

From individual advancement with a wide range of continuing education opportunities to a variety of health and recreational offerings, you can expect an appreciative working environment at a renowned university at TU Ilmenau. In addition to an attractive, familyfriendly working hours model, you will also benefit from advantages such as the use of the dining halls of the Studierendenwerk Thüringen, as well as participation in the various attractive sports offerings of the University Sports Center.