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coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
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Institute focusing on ice pile-ups and related risks to coastal structures and erosion. The ice rubble piles form as sea ice is pushed by wind towards the coastlines, fractures and fractured ice
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films. The position is part of an ambitious collaborative research effort at Aalto University and the Finnish Meteorological Institute, bringing together molecular-scale surface engineering, advanced
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-sensitive networking). The work is funded by a Finland-US joint project in partnership with MIT, Stevens Institute, Nokia Bell Labs, and pilots with leading Finnish companies. Supervisor: Assistant
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Institute of Informatics in Japan, Prof. Xavier Serra at Universitat Pompeu Fabra in Spain, Prof. Gustav Eje Henter at KTH Royal Institute of Technology in Sweden. The collaboration network has a
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Technology, KTH Royal Institute of Technology and TUL Montanuniversität Leoben, so your work will be discussed both in the scientific community and with the people planning Finland’s hydrogen
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doctoral researcher(PhD student) with a strong background in probabilistic machine learning, statistics, applied mathematics, computer science, or a related field, and strong programming skills, to
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more of the following areas: Stochastic processes, ideally including a background in ergodicity theory; Reinforcement learning, dynamic programming, and Markov decision processes; Programming skills
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with the E-sail payload from the Finnish Meteorological Institute (FMI), as well as the DR will develop new and improved in-orbit E-sail experiments for future missions in lunar orbit and deep space. The
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with signal processing, time series analysis or machine learning Programming skills in MATLAB and/or Python What we offer The position is fixed term and follows Aalto's standard 2+2 model. It will be