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and visual monitoring during deployment, working in coordination with the RT3D development led by E-Sailor 15. The research includes conducting laboratory and in-orbit experiments using data from
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We consider the following an advantage: experience in handling register data, databases or large datasets, especially experience with sensitive data or secure research environments knowledge of health
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activity using fully compressible MHD in global and local frameworks, integrated with physics‑informed machine learning and coronal/wind modelling. Key tasks and responsibilities: Develop and implement data
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consider candidates who have not submitted applications during the application period. Further information Professor Jukka Suomela, e-mail "[email protected] " (research-related information) HR Advisor
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Jukka Suomela, e-mail "[email protected] " (research-related information) HR Advisor Susanna Holma, e-mail "[email protected] " (recruitment process; not available July 3–23) Want to know more about us
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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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23 Jul 2026 Job Information Organisation/Company AALTO UNIVERSITY Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline 14 Aug 2026
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. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning
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such as breakwaters by using computational tools developed in our research group. These tools are based on discrete element method and they have bee validated against experimental data. You will start your
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community. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure