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of Finland under the supervision of the Academy Research Fellow Marcelo Hartmann and Research Fellow Luu Hoang Phuc Hau (Nanyang Technological University). We have been developing computational algorithms
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computational algorithms and theory grounded in notions of information geometry and Riemannian geometry to enhance Bayesian statistical inference and machine-learning related methods. The successful deployment
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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algorithm development using Python or equivalent programming languages is considered an asset. Given the highly international and collaborative nature of the research environment, strong presentation and
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and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with
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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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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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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