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convection, extra-tropical cyclones, and ensemble prediction including algorithmic parameter estimation. The group’s main modelling tool in research and teaching is OpenIFS of ECMWF. Research within
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research group at INAR, led by Professor Heikki Järvinen. The group is active in topics such as atmospheric convection, extra-tropical cyclones, and ensemble prediction including algorithmic parameter
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to next-generation 2D gas sensors. You will manage large-scale simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with
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atmospheric deep convection, extra-tropical cyclones, heat waves, ensemble prediction and algorithmic parameter estimation techniques as well as future changes to our weather and climate on global and regional
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at FIMM, led by Simone Rubinacci, develops methods for large-scale human genomics and statistical genetics. Our work spans algorithm development, cloud computing, and population-scale sequencing
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algorithms that feature built-in verifiability and robust defensive capabilities. Collaborate closely with top-tier European universities and industrial partners. Participate in project implementation and
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the intersection of statistical signal processing and optimization, with an emphasis on theory and algorithms. Key focus applications include array signal processing for sensing (e.g., radar, RF imaging, sonar) and
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group at INAR , and be supervised by Dr. Clément Bouvier. The group covers a range of topics including atmospheric deep convection, extra-tropical cyclones, heat waves, ensemble prediction and algorithmic