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model improves the prediction of additional losses introduced by the manufacturing process. The successful candidate will contribute to research on generalizing some advanced magnetic material model
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system. The project is carried out in collaboration with Wärtsilä, which provides powertrain data, operational torsional-dynamics measurements for model verification, and access to a physical maritime
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developing the code to include time dependent cohesive bonding between the ice blocks. Then you will use the code to model ice pile-up. The work will have a multi-scale component as you will combine your
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analyse large‑scale global solar/stellar dynamo simulations capable of capturing both small‑scale and large‑scale dynamos in the same model with resolutions requiring at LUMI‑class resources. Perform
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shared industrial spaces. The research will model how people and machines move through dynamic environments to support human detection and tracking, spatio-temporal mapping, long-horizon human-motion
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position is fixed term and follows school’s standard 2+2 model. It will be made initially for two years, with a six-month probationary period, and extended by two further years after a successful mid-term
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you design a model in the morning and pressurise real rock underground in the afternoon. Join us in shaping a more sustainable future! Your role and goals Integrating geological datasets and applying
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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
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machine learning, and/or publication record in machine learning or security/privacy, software supply chains. What we offer We offer a fully funded position (2 + 2 model) under the supervision of
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and follows Aalto's standard 2+2 model. It will be made initially for two (2) years, with a six (6) month probationary period, and extended by two (2) further years after a successful mid-term review