Job Offer: Research Assistants in the Context of the DFG Project nfdi4energy

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Computer Science 7 (Computer Networks and Communication Systems) of Friedrich-Alexander-University Erlangen-Nürnberg (FAU) is looking for

two Research Assistants (m/f/d)

in the context of the DFG project nfdi4energy (National Research Data Infrastructure for Interdisciplinary Energy Systems Research).

Your tasks:

Improving the communication and exchange of data and software in energy systems research is the goal of the nfdi4energy consortium (nfdi4energy.uol.de) with numerous scientific partners. The German Research Foundation (DFG) is funding the project with up to ten million euros, initially for five years. FAU will coordinate the Task Area “Simulation in Interdisciplinary Energy Research” in the consortium. The overall goal of this task area is to better support the use of simulations in the energy field for both experts and interested non-experts. For many advanced research questions, it is necessary to perform distributed simulations. Therefore, an important goal is to better support the execution of distributed simulations by offering Simulation-as-a-Service (SaaS) with the nfdi4energy platform as a front-end. In doing so, the following two tasks will arise at FAU, each of which can be performed by a PhD student or a postdoctoral researcher, respectively:

In the scope of the first task, an existing framework for loosely coupling different simulators is extended to meet the requirements from nfdi4energy. Therefore, a concept needs to be developed as well as implemented. Although the framework was designed in a general way, its primary use was in the mobility domain. Therefore, one issue is the adaption to the modalities of the energy sector. The approach also provides SaaS capabilities, which shall also be extended to fit with the intended use cases of other Task Areas. Communication networks as a part of an energy system needs to be integrated and can be modelled at various abstraction layers: in a direct approach a packet-level communication network simulator such as OMNeT++ or ns3 is used, as an alternative approach the quality-of-service characteristics can be represented inside another simulator by its statistical properties, possibly derived by using machine learning.

In the scope of the second task an existing aggregation/disaggregation approach which takes into account individual constraints (with respect to power, energy, and time) of electric vehicles of a larger fleet and can efficiently compute the ability to provide flexibility over time without violation of any individual constraint. It is intended to adapt this approach in terms of assets (besides electric vehicles also stationary batteries of households can be considered), bidirectionality (currently charging is restricted to be unidirectional), uncertainty (instead of deterministic demands random profiles of the individual components), combination of centralised and decentralised control, and resilience (operation under impairments of the communication).

Necessary qualifications:

  • Over-average master’s degree in Computer Science, Energy Technology or a related field of study
  • Motivation to work in an academic context
  • Very good skills in communication and team work, reliability
  • Interest to work in the mentioned research fields
  • English language skills to work with scientific partners

Formalities:

  • Full-time position according to E 13 TV-L (without PhD) or E 14 TV-L (with PhD)
  • For a limited time of three years, can optionally be extended by two years
  • Obtaining a Ph.D. degree is possible
  • Operating place is Erlangen

Supplementary information:

  • Planned start: March 1, 2023
  • Applications: immediately, no deadline

For more information please contact:
Reinhard German, professor
Department Informatik, Lehrstuhl für Informatik 7 (Rechnernetze und Kommunikationssysteme)
Phone +49.9131.85.27916, Fax +49.9131.85.27409, E-Mail: reinhard.german@fau.de

In its pursuit of academic excellence, FAU is committed to equality of opportunity and to a proactive and inclusive approach, which supports and encourages all under-represented groups, promotes an inclusive culture and values diversity.