30 doctoral researcher and 3 postdoc positions in CRC/TRR 391



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Postdoc, phd candidate

The newly founded Collaborative Research Center (CRC) TRR 391 "Spatio-temporal Statistics for the Transition of Energy and Transport" at TU Dortmund University and Ruhr University Bochum (with participation of the Universities of Duisburg-Essen, Hamburg, Münster, KIT Karlsruhe, TUHH Hamburg, FH Dortmund, and the RWI Leibniz Institute for Economic Research Essen) is inviting applications for 30  doctoral researcher and 3 postdoc positions (f/m/d) starting on October 1st, 2024. The positions will be funded by the German Research Foundation (DFG) until June 2028.

Our CRC/TRR 391 is highly interdisciplinary, integrating data-driven and knowledge-driven modeling approaches from statistics, data science, mathematics, computer science, electrical engineering, economics, and transportation/logistics, to create comprehensive solutions for tackling urgent problems arising in the transition to a low-carbon economy and renewable economies. The CRC/TRR 391 models, estimates and predicts spatio-temporal processes occurring in economic and technical applications. In doing so, we exploit the formal similarity of relevant statistical problems for methodological synergies and develop key techniques for the analysis of spatio-temporal data, which will enable efficient data-based decision-making in various areas of the energy and transport transition in the next decades. All doctoral researchers will become members of our integrated research training group STAIRS for fostering interdisciplinary exchange and establishing a shared language between disciplines.

You can look forward to:

* An excellent research environment and a vibrant interdisciplinary community

* Research that pushes the boundaries of what can be achieved in spatio-temporal data settings with statistical modeling techniques and artificial intelligence

  * Structured supervision and courses that will prepare you for excelling within the respective disciplines, but also for crossing borders between them, including transferable skills and career development

  * A welcoming and international research campus with a long tradition of interdisciplinary work in the data sciences

The successful candidates will work at the institutions running the different subprojects of our CRC/TRR 391, please see the list of such subprojects below.

The prerequisite for a PhD appointment is a diploma or master’s degree in statistics or data science, or alternatively mathematics, computer science, electrical engineering, economics, logistics, geoinformatics or related programs (with a focus on statistics or data science).

The prerequisite for a PostDoc appointment is a PhD in statistics or data science, or alternatively in mathematics, computer science, electrical engineering, economics, logistics, geoinformatics or related programs (with a focus on statistics or data science).  Seriously disabled persons will be favored in case of equal qualification. Women are explicitly encouraged and will be favored in case of equal ability and professional performance.

Please send complete applications with the usual documents (curriculum vitae, diplomas, list of publications if applicable) including a motivation letter that also prioritizes typically up to three of the TRR research projects until July 20, 2024, to TRR391@statistik.tu-dortmund.de


List of subprojects:

Area A Statistical methodologies for spatio-temporal data

A01  Optimal designs for spatio-temporal data   Holger Dette (RUB Bochum), Kirsten Schorning (TU Dortmund)

A02  Space-time in high dimensions   Axel Bücher (RUB Bochum), Andreas Groll (TU Dortmund), Johannes Lederer (UHH Hamburg)

A03  Resampling and model validation for spatio-temporal data Holger Dette (RUB Bochum), Carsten Jentsch (TU Dortmund)

A04  Statistical monitoring of spatio-temporal processes  Roland Fried (TU Dortmund), Vasyl Golosnoy (RUB Bochum)

A05  Deep learning in space and time  Asja Fischer (RUB Bochum), Johannes Lederer (UHH Hamburg), Hanna Meyer (University Münster)

A06  Forecasting methods for spatio-temporal data: robust evaluation and inference  Matei Demetrescu (TU Dortmund), Christoph Hanck (UDE Duisburg-Essen)

A07  Distributional copula regression for space-time data  Holger Dette (RUB Bochum), Nadja Klein (KIT Karlsruhe)


Area B  Statistics for the transport of energy and goods

B01  Statistical modeling and analysis for state estimation in electrical power distribution grids  Christine Müller (TU Dortmund), Christian Rehtanz (TU Dortmund)

B02  Statistical methods for energy systems: aggregation and decomposition  Timm Faulwasser (TUHH Hamburg), Roland Fried (TU Dortmund)

B03  Uncertainty quantification for decision support in transport logistics systems  Uwe Clausen (TU Dortmund), Sonja Kuhnt (FH Dortmund)

B04  Real-time spatio-temporal data analysis for monitoring logistics networks Paul Bürkner (TU Dortmund), Anne Meyer (KIT Karlsruhe), Edzer Pebesma (University Münster)


Area C Econometrics of the energy and transport transition

C01  Energy price shocks: identification, transmission, and induced technological change  Christoph Hanck (UDE Duisburg-Essen), Carsten Jentsch (TU Dortmund), Ludger Linnemann (TU Dortmund)

C02  Renewable energy forecasts and their impact on electricity prices Antonia Arsova (TU Dortmund), Florian Ziel (UDE Duisburg-Essen)

C03  Monitoring of Germany’s mobility transition: data and methods Matei Demetrescu (TU Dortmund), Manuel Frondel (RWI Essen), Colin Vance (RWI Essen)

C04  Targeting energy conservation  Mark Andor (RWI Essen), Asja Fischer (RUB Bochum), Andreas Löschel (RUB Bochum)


Supporting projects

INF  Information infrastructure project  Paul Bürkner (TU Dortmund), Andreas Groll (TU Dortmund), Sandra Schaffner (RWI Essen)

MGK STAIRS – Spatio-temporal analysis interdisciplinary research school  Carsten Jentsch (TU Dortmund), Kirsten Schorning (TU Dortmund)

Z  Central administrative project  Roland Fried (TU Dortmund)

More Information

Posted on

Start Date

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Postdoc, phd candidate