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HIL environment rather than only on offline simulation. Learning outcomes anticipated include stronger understanding through immediate feedback on live systems, deeper engagement with
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Information Management, or related fields; Have basic knowledge of machine learning models in supervised and unsupervised learning tasks (i.e., k-nearest neighbours, Decision Trees, Neural Networks, Logistic
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application Deadline 14 Jul 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Not Applicable Job Status Not
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Advisor: João Paulo Lopes Monteiro (ist169647) Organic Unit: Department of Electrical and Computer Engineering Scholarship Theme: Software development for 5G Nanosatellite mission Duration: 12 months
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automated detection models (deep learning and/or classical) for ROI identification from lower resolution or degraded MRI data Develop simulation frameworks to generate realistic low-resolution or motion
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: Opportunities through UF Training & Organization Development, leadership development, LinkedIn learning, and more PSLF Eligibility: We are a Public Service Loan Forgiveness Eligible Employer Click here to learn
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will be immersed in a unique learning environment at the interface of clinical research, neurocritical care, and data analysis. This three-year fixed-term post as a university assistant (PraeDoc
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
impact in the field of plasma physics, catalysis and electrolysis. By carrying out cutting-edge research, the students will not only acquire crucial skills for their future, but also scientifically
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domain knowledge in 4 core application domains, for which reliable AI methods are most urgently needed: medicine and healthcare, robotics & interacting systems, algorithmic decision-making, and learning
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-technical systems and human-machine interaction All applicants must demonstrate an above-average academic track record, typically with a cumulative grade point average of 1.7 or better (after conversion