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?
We look forward to receiving your application documents (English or German); applications should include:
- 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)
- Names and email addresses of 2-3 academic references
Please send the application as a single PDF document via e-mail to esm@ei.tum.de, with “Application GHG Modeling” as the subject line. Applications will be reviewed until the position is filled.
Further info about the research group: www.ee.cit.tum.de/esm.
If you have any questions about the position, please contact us: esm@eesm@ei.tum.de.i.tum.de.
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Kontakt: esm@ei.tum.de
https://www.ee.cit.tum.de/esm/startseite/