We are recruiting for the position of a PostDoc / Senior Researcher (f/m/d) in the field of Statistics and Machine Learning, starting from October 2021 or later. The position will be within the research group for Mathematical Statistics in the Department of Mathematics at the Technical University of Munich (TUM) and part of MaRDI (Mathematical Research Data Initiative). MaRDI aims to set standards for certified mathematical research data, the design of confirmable workflows, and it provides services for the scientific community. MaRDI is part of the German Research Data Infrastructure initiative (NFDI programme).
The position will be part of the Task Area "Statistics and Machine Learning”, which is represented at TUM by Prof. Mathias Drton and Dr. Stephan Haug. Particular tasks will be the design, implementation, population and management of a library of curated benchmark datasets and statistical analyses. Within the project, the guiding use cases will be from the field of unsupervised model selection in graphical modelling.
Qualifications and Skills:
The candidate should be highly self-motivated, be interested in tackling challenging research problems, have organisational skills, be open minded, and have scientific leadership potential. For queries or further information please contact Dr. Stephan Haug (firstname.lastname@example.org).
We offer an interesting, varied and challenging position within a young, international and interdisciplinary team located at the Garching-Hochbruck Campus of the TU München. The contract will have an initial duration of 2 years with the option to extend the contract for up to 3 further years. The position is paid according to the Civil Service rates of the German States “TV-L”, E13 (if suitably qualified) at 100% of the regular working hours.
How to apply: Applications should be sent as a single PDF file to Andrea Grant (email@example.com) using subject: "MaRDI Application". The file should include:
As an equal opportunity and affirmative action employer, TUM explicitly encourages applications from women as well as from all others who would bring additional diversity dimensions to the university's research and teaching strategies. Preference will be given to disabled candidates with essentially the same qualifications.
Applications will be reviewed as they are received and the review will continue until the position is filled.
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