172 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions in Finland
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society. Central themes of teaching and research include Digitalisation, Machine Learning, Autonomous and Intelligent Systems, Cybersecurity and Health Technology. The Faculty of Technology is the newest
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microelectronic hardware. Preclinical in-vitro and in-vivo testing of devices and methods will allow real world validation of this unusual Brain-Computer Interface. More information: (7) BRAINET: Overview
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of Helsinki, part of the INSTRUCT-HILIFE structural biology platform (including the cryoEM, protein crystallization and biocomplex purification units). The salary range is 3,300-4,300 €/month, the position is
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note that, the selected candidate must apply for a study right within the doctoral program at Tampere University, unless they already have one. Please visit the admissions webpage https://www.tuni.fi/en
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professors. To learn more, please visit eng.aalto.fi . The Department of Energy and Mechanical Engineering at the Aalto University School of Engineering invites applications for Doctoral researcher on energy
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into the UTUGS doctoral programme, the title will be updated to doctoral researcher. Eligibility requirements for these positions are defined in the University of Turku's regulations: https://www.utu.fi/en
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professor will be an active and visible contributor to regional, national and international research cooperation, and will acquire external funding, build a strong research portfolio and foster internal
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, advanced simulations, and machine learning to study emergent quantum phenomena in platforms such as ultracold atoms, molecules, and photonic devices. Its research develops new frameworks and computational
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competence development opportunities. Read more about us: https://www.uwasa.fi/en/open-positions The salary is based on both the job requirement and the employee’s personal performance in accordance with
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-driven 3D motion understanding and generation in the following ways: Developing machine learning methods to decode EEG-based motor imagery for 3D human motion reconstruction, focusing on latent diffusion