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) . Names and contact details for two references Additional relevant documentation of professional knowledge (for example, list of scientific works). If it is difficult to judge the applicant’s contribution
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(HORIZON) Doctoral Networks, ‘Bridging Communication Gaps in Human and Human-AI Interactions: The Role of Accented Speech on Neurocognitive mechanisms and Social Dynamics’ (HUM.AI.N-ACCENT) Location
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master's students, and contribute to the dissemination of research findings. Work closely with computer scientists, statisticians, and neurologists to ensure both clinical relevance and methodological
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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environment with the opportunity to network with both the business community and international contacts. More information about the department: Department of Applied Animal Science and Welfare Read more about
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experiment. This PhD position is embedded in the EU Horizon Europe Marie Sklodowska-Curie Doctoral Network (MSCA DN) SMARTTEST project. This position is linked to Doctoral Candidate 8 – DC08. For more
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Human-AI interaction. Your network and team The Aalto Engineering Psychology Group concentrates on research in human-AI interaction . Currently, research activities focus on applying research methods from
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» Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain Application Deadline 19 Sep 2025 - 23:59 (Europe/Madrid) Type of Contract Temporary Job Status Full
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 8 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially