Scientific Researcher
vor 7 Monaten
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)
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