157 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" Fellowship scholarships
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2nd September 2025 Languages English Norsk Bokmål English English Faculty of Biosciences, Fisheries and Economics PhD Fellow in Impact of Temperature on Embryonic Development of the stress axis in
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 17 days ago
-FEDER-00818200 and the acronym flexREC, financed by FCT, the European Regional Development Fund and national funds through the program MPr-2023-12l, in the following conditions: Scientific area
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applying Natural Language Processing (NLP) algorithms. Knowledge or prior experience in Virtual Reality technologies. Work Plan: The grant aims to develop Agricultural Simulations using Virtual Reality as a
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the methodologies for preventing unintended, harmful behaviors in open-source AI models. Your work will focus on the foundational challenges of safety, from mitigating algorithmic bias to ensuring systems remain
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that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in