Committees

In order to promote the broad activities of the Cluster, Committees were established whose members conceptualize and pursue the various measures in their respective committee.

The Research Committee ensures that competitive procedures are followed and the highest standards are applied in the Cluster when

  • filling positions on all levels,
  • monitoring the personal development of SimTech’s academic staff,
  • funding research projects,
  • evolving research structures,
  • monitoring research performance, and
  • enforcing software quality standards and controlling research data management.

It encompasses a broad range of activities:

  • Yearly supervision, monitoring and consulting by the Advisory Board, e.g., with regard to the designation and selection of new professorships and Junior Research Groups, Project Network creation and termination, and monitoring structural measures.
  • A strict peer review process involving external experts before funding is granted to project proposals.
  • Yearly status seminars and additional termly seminars, in which all projects and Project Networks are required to present their results.
  • A mid-term peer review evaluation process involving the Advisory Board and international experts based on status reports of the projects and the entire Cluster.
  • Continuous consultancy and cooperation with the University’s central department for quality assurance, which is responsible for system accreditation, further quality assurance measures, academic controlling, and research information systems.
  • Personal development consulting for staff, specifically for young scientists.

The committee for Academic Affairs is responsible for the quality assurance of the study programs which are offered by the SC SimTech. It develops further and adapts the study and admission regulations. Furthermore, new study programs in the area of data-integrated simulation science are drafted. The current study programs of the SC SimTech are the BSc Simulation Technology and the MSc Simulation Technology.

This committee provides advice to the executive board in all matters of the doctoral program and of early-career researchers. This includes the structure and the rules of the Graduate School Simulation Technology, as well as support and the implementation of rules provided by the university for doctoral students, postdocs, junior group leaders and junior professors.

The committee for Research Data & Software Management develops infrastructure and guidelines for data and software management. Therefore, two positions were established for SimTech. A Data and Software Steward, who develops strategies, workflows, standards and best practices for SimTech’s research data management (RDM) and research software engineering (RSE) activities, and a Research Software Engineer for RDM, who develops, administers, and consults on technical solutions for improving SimTech’s research data management (RDM) and research software engineering (RSE) activities.

The committee encourages and supports RDM principles and infrastructure within the SimTech research groups. The efforts are tightly integrated with the activities of the university's Competence Center for Research Data Management (FoKUS), such as  the local infrastructure DaRUS (Data Repository of the University of Stuttgart). The DaRUS platform provides data and software, together with all technical services for uploading, hosting, sharing, publishing, archiving, and searching research data. Furthermore, a forum for SimTech PIs, postdoctoral fellows and PhD students planning to improve their research data infrastructure has been implemented. The Special Interest Group on Data Infrastructure at the University of Stuttgart (SIGDIUS) meets monthly (Wednesday, 2 - 4pm) to discuss about the specific needs, become aware of the data to be managed, learn about (dis)advantages of commercial and open source solutions and engage in establishing community standards.

Another aim of the committee for Research Data & Software Management is to strengthen simulation-related aspects in overarching RDM entities. Thus, several SimTech members are already active in the discipline-specific consortia (MaRDI, NFDI4Chem, NFDI4Ing and NFDI4MS) for the establishment of the national research data infrastructure (NFDI).

Within the Cluster of Excellence, the board for "Experimental platform and central hardware" plans and coordinates acquisition and shared usage of core experimental platforms and central computational facilities. Within the EXC 2075, a new experimental CPU- and GPU-cluster is planed for 2020/2021. The cluster is to be used for medium-scale simulation and machine learning tasks as well as for the preparation of software for the transition to the supercomputing facilities at HLRS. 

Core experimental facilities of the Cluster include the Porous Medium Lab, the Multiphase Flow Lab, the Neuromechanics Lab, the Pervasive Simulation Lab and the Experimental Compute Lab.

We are committed to actively seek and integrate new collaborations and sincerely foster the existing and newly established ones. This does not only include to foster national and international scientific collaborations with renowned institutions, but also the promotion of staff and student exchanges during all stages of their career. Strong networks are instrumental for driving and sustaining a new field of research.

The aim of the committee for knowledge transfer is a collaboration between university and industry. One example of this is the registered association "Industrial Consortium SimTech e. V." whose members are well-known companies of Baden-Württemberg as well as the SC SimTech. By joint meetings and projects it is the goal to combine the fundamental research of the university with the real-world applictions of the industry.

Data abundance, privacy, and dual-use are just a few of the important societal, social or ethical issues that do also come up in the context of simulation science. The Excellence Cluster Data-integrated Simulation Science and the corresponding Research Centre at the University of Stuttgart are committed to take responsibility concerning those topics. For this a Platform of Reflection has been established that raises awareness among the involved researchers and also beyond, monitors the research within the Cluster and actively pursues contextualization with a broad involvement. The Cluster's Platform of Reflection is tightly interwoven with the corresponding activities within the University as a whole and the tasks of this committee include actively shaping this connection.

Machine Learning (ML) is a core aspect for the success of data-integrated simulation science. This committee will provide information and realize activities with respect to ML in the simulation context. We will disseminate ML knowledge and technology within SimTech and support its networking and collaboration.

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