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for demanding terrestrial and non-terrestrial (Aerospace) applications accounting for sources of variability and uncertainty, for example, those arising from material, fabrication process, and boundary and
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include training in computer science, human-computer interaction, etc. A Master’s degree is desirable. In addition, candidates for whom English is a second language should meet the University’s minimum
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for Real-World Optimisation and AI Applications Brain-Computer Interfaces & their Applications Computational Neuroscience: Reinforcement Learning and Microzones in the Cerebellum Explainable Generative
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researcher to experimentally investigate condensation processes at surfaces with molecular precision. The work focuses on developing advanced methods for controlling wetting and nucleation, combining cutting
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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-processing crucial. However, video restoration and enhancement are complex due to information loss and the lack of ground truth data. This project addresses these issues innovatively. We propose using prior
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application process, and to consider candidates who have not submitted applications during the application period. Further information Want to know more about us and your future colleagues? You can watch these
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information in recruitment process related questions, please contact HR Advisor Johanna Haapalainen, hr-elec@aalto.fi . Want to know more about us and your future colleagues? You can watch these videos: This is
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help
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device nanofabrication and clean room processing of 2D materials (required). Skill sets of handling low-temperature and ultra-high vacuum systems, such as molecular beam epitaxy (MBE) or STM experience