Postdoctoral Researcher

vor 3 Monaten


Eichstätt, Deutschland Katholische Universität Eichstätt-Ingolstadt Vollzeit

The Chair of Applied Mathematics within the Mathematical Institute for Machine Learning and Data Science (MIDS) at KU Eichstätt-Ingolstadt invites applications for a fulltime position (100%) for a
Postdoctoral Researcher in Applied Mathematics/Fluid Dynamics (m/f/d)
to be filled from the earliest possible starting date. The place of work will be Ingolstadt. The successful candidate will be employed in a private-law employment relationship, in which case remuneration will be according to pay grade E 13 TV-L provided that the requirements are met.
The position is funded by and shall contribute to the Collaborative Research Center TRR 181 »Energy Transfers in Atmosphere and Ocean« for a duration of up to four years parallel to approved German Research Foundation funding periods. TRR 181 is a collaborative project between Universität Hamburg, Universität Bremen, KU Eichstätt-Ingolstadt, the Alfred-Wegener-Institut Bremerhaven, the GEOMAR Helmholtz Centre for Ocean Research Kiel, and several other partner institutes.
Physical oceanographers, meteorologists, and applied mathematicians are working together in the project

to understand the energy transfers between the different dynamical regimes - small-scale turbulence, internal gravity waves, and geostrophically balanced motion - in both atmosphere and ocean,
to develop, to test, and to implement new and consistent parameterisations in models, and
to develop mathematical and numerical methods featuring consistent energetics.

The goal are energetically more consistent climate models for advanced climate predictions.
Your tasks

Scientific contributions toward work package 2 on «Mode Interactions and Optimal Balance» in subproject L2 «Quantifying Dynamical Regimes in the Ocean and the Atmosphere»
Contributions toward the overall goals of subproject L2 and the TRR 181 at large
Independent research and publications in applied mathematics
Participation in the research activities of the group

Your profile

Excellent PhD degree in one of the relevant areas of applied mathematics
Ability to work in a team
Ability to structure and pursue a successful research agenda
Flexibility and willingness to travel
German language skills are not required, but candidates are encouraged to develop those during their employment at the KU

Our offer

Participation in the development of the newly founded Mathematical Institute for Machine Learning and Data Science (MIDS)
Entrainment into a vibrant interdisciplinary collaborative research network
Team-oriented and well-equipped work environment in central Ingolstadt
Opportunity and support for career development

Your application
Please send your application with the usual supporting documents by e-mail to Prof. Dr. Marcel Oliver (marcel.oliver@ku.de). Please combine all documents in one PDF file. Applications received by July 07, 2024 will receive full consideration. Your documents should include cover letter, curriculum vitae, copies of transcripts and degree certificates and at least one letter of recommendation.
All application documents submitted will be destroyed/deleted after completion of the hiring process in compliance with data protection regulations. Please note the KU's privacy policy for the application process. Corresponding information can be downloaded from the KU website at By submitting your application, you confirm that you have taken note of the data protection information and the privacy policy.
All employees are obliged to acknowledge the nature and mission of the KU as stipulated in its Mission Statement and Foundation Charter. The University is therefore interested in receiving applications with relevant information in this regard. There are no specific denominational requirements for being employed at the KU.
The KU is committed to promoting equal opportunity (m/w/d), and aims to ensure that its members are able to balance work and family life. Candidates with severe disabilities (m/w/d) who are equally suitable to other applicants will be prioritized.
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