Scientific Researcher

vor 1 Woche


Munich, Deutschland Technische Universität München Vollzeit

TASKS:

- Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on ℓ1-norm minimization and compressed sensing) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: atmos
- phere.ei.tum.de/) and in-situ sensor networks in ICOS Cities project (icos-cp.eu/projects/icos-cities)
- Design and implementation of suitable algorithms, using the High Performance Computing infrastructure at Leibniz Rechenzentrum (LRZ)
- Analysis of ground-based and satellite-based remote sensing data
- Presentation of your results at conferences and publications in scientific journals

**REQUIREMENTS**:

- An above-average degree in mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification
- Very good knowledge of mathematics, especially in linear algebra and numerical optimization
- Understanding of statistical modeling and inverse problems is desirable
- Experience with programming languages, e.g., C++, MATLAB, Python, Julia, R
- Joy in dealing with challenging and interdisciplinary questions
- Sound knowledge of written and spoken English. Basic German knowledge desired.

WE OFFER:

- Exciting research questions within a reputable ERC Consolidator Grant
- Possibility of earning a doctoral degree
- Access to an excellent international network and up-to-date research topics
- Opportunities to work with the top peers from Harvard University, NASA JPL, UC Berkeley, and other European partners, e.g. LSCE (France), EMPA (Switzerland)

INTERESTED?
- Detailed CV, including previous publications if applicable
- Motivation describing research interests and goals (one page)
- A list of previously taken courses and grades
- Summary of master thesis (not more than one page)

**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.

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