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Technical University of Munich

Wissenschaftliches Personal

 
Technische Universität München

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WorkplaceMünchen, Bayern, Germany
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Technische Universität München


Technische Universität München

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Wissenschaftliches Personal

19.01.2020, Wissenschaftliches Personal

The TUM Department of Mathematics is establishing the TUM Data Innovation Hub (TUM-DI-HUB) as a platform to connect research and teaching in data science to practice and cooperation with partners from industry.In the context of the TUM-DI-HUB, we are announcing the opening of an international position for a Doctoral or PostDoctoral Researcher to provide the expertise required for the planned expansion of the consulting services and assist with coordination of the TUM-DI-HUB.

The TUM Department of Mathematics is establishing the TUM Data Innovation Hub (TUM-DI-HUB) as a platform to connect research and teaching in data science to practice and cooperation with partners from industry. The TUM-DI-HUB will bundle, coordinate, and subsequently expand the existing activities of the Department of Mathematics in the field of data science. Its activities will include (a) research conducted in the framework of the newly established Munich Data Science Institute (MDSI), (b) teaching in the Master of Mathematics in Data Science program, (c) the TUM Data Innovation Lab’s (TUM-DI-LAB) student research experiences, and (d) the department’s consulting services, DI.consult.

In the context of the TUM-DI-HUB, we are announcing the opening of an international position for a Doctoral or PostDoctoral Researcher to provide the expertise required for the planned expansion of the consulting services and assist with coordination of the TUM-DI-HUB. The position is to be started no later than April 1, 2020, and will be co-supervised by Professors Mathias Drton (Mathematical Statistics) and Massimo Fornasier (Applied Analysis and Numerics).

Ideal candidates have the following profile: o Doctoral/PostDoc candidate, trained in mathematics, mathematical statistics or computer science, o Consolidated and certifiable knowledge of deep learning and its practice (included related programming languages such as, for example, Tensorflow, Keras, Theano, PyTorch and related visualization software), o Strong interest in industrial cooperation.

We offer an interesting, varied, and challenging position, which combines development of know-how with industrial research and cooperation within an experienced international team. The position is paid according to the Civil Service rates of the German States "TV-L", E13 100% (if suitably qualified). The contract is initially limited to a two-year period, with a possible extension provided the availability of funding. For further information, please contact Mathias Drton (mathias.drton [at] tum[.]de) or Massimo Fornasier (massimo.fornasier [at] ma[.]tum[.]de).

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 should include: o a complete Curriculum Vitae, o copies of degrees / university transcripts, o a motivational statement (at most one page) explaining the applicant’s interest in the position as well as their relevant skills and experience, o name and email address of at least one Professor who may provide a letter of recommendation directly to the hiring committee.

Applications should be sent as a single PDF file to: grant [at] ma[.]tum[.]de. Please indicate "TUM-DI-HUB Researcher" in the subject line.

The review of applications will begin on February 1, 2020 and continue until this position is filled.

Hinweis zum Datenschutz:
Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.

Kontakt: Mathias Drton, Massimo Fornasier

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In your application, please refer to myScience.de and reference JobID 152858.


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