HDS-LEE graduate school

HDS-LEE is an international, English-speaking graduate school in the ABCD (Aachen-Bonn/Cologne-Düsseldorf) triangle of North-Rhine-Westphalia. HDS-LEE is part of the newly founded JARA Center for Simulation and Data Sciences (JARA-CSD), which will be created as a unique, internationally visible competence center for computer- and data-infrastructures, user support as well as methodological and disciplinary research in the fields of simulation, data analysis and HPC technologies. More specifically, the School for Simulation and Data Sciences (SSD) within JARA-CSD has the training of doctoral students as its focus and brings together leading researchers from university and research centers and fosters interdisciplinary supervision of the graduate students. Furthermore, HDS-LEE students will benefit from the international recognized regional graduate schools GRS and AICES, which were fused under the roof of JARA-CSD. As part of the Helmholtz Information & Data Science Academy (HIDA), attractive events and courses will be opened to doctoral researcher as well as student exchanges and symposia will be facilitated between the other HIDA graduate schools.

The school aims at excellent mathematics, computer science, natural science and engineering graduates who strive to advance the development of data science methodologies and harness the power of state-of-the-art data science technologies to solve challenging scientific problems in the three application domains. The objective of HDS-LEE is to educate, train and support talented scientists during their doctoral thesis.

The graduate school will provide funding for 24 doctoral student positions. Doctoral researchers benefit from the interdisciplinary supervision and mentoring concept and the clearly-structured doctoral program. A coordinator team (one at RWTH and one at FZJ) act as the central point of contact for the students with regard to all organizational and administrative issues.

Scientific curriculum

The central education and training concept behind HDS-LEE is to train doctoral students with respect to all essential elements of information and data sciences. The scientific qualification concept in HDS-LEE is augmented by a comprehensive portfolio of mandatory and elective modules for transferable skills and career advancement.

Scientific supervision and mentoring of doctoral students is provided by individualized thesis advisory committees. Such a committee is comprised of the two PIs who have initiated the doctoral project and a scientific co-advisor. Doctoral students will be hosted by the institutes of their PIs to enhance communication and exchange with the respective research groups.

An integral part of HDS-LEE is the curriculum of joint activities, which includes a block course on data science methodologies and applications, annual retreats, and an annual conference. Training days at the Jülich Supercomputing Center (JSC) constitute another key element of the HDS-LEE concept. Here students receive expert knowledge on a wide range of topics such as parallel computing, machine learning, and visualization. The joint activities (i.e., block course on data science fundamentals, international conferences, and internal retreats) also essentially contribute to overcoming the geographical distances between the doctoral researchers

Towards the end of the doctoral program, there is the possibility to perform an industrial internship while on a leave of absence from the host institution. Additional modules can be included into the curriculum, e.g., a stay abroad, which have to be agreed upon.