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, gender, gender identity or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected
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on infrastructure degradation, maintenance needs, operational risk, punctuality and costs. The aim is to develop and validate a practical, transparent benefit-assessment tool for selected TrainGate cases. It will
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spectrum of topics in CNU sections 27 "Computer Science" and 61 "Computer Engineering, Automation and Signal Processing". The laboratory is located at the heart of the Sophia Antipolis technology park, in a
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | 3 days ago
Do you want to help transform human health through machine learning and life science approaches? Join AITHYRA in Vienna for a fully funded PhD at the intersection of machine learning, experimental
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, simulation or analysis of electrical machines or electric drives, such as BLDC/PMSM systems Essential Application/interview Experience using engineering software or programming tools for modelling and data
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depends on complex, interconnected systems such as sustainable power grids, autonomous vehicles and human-machine collaborative systems. Ensuring that these systems operate safely, efficiently and fairly is
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://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large
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develop our own numerical methods and tools, but also extensively employ and co-develop numerical techniques provided by the international community. We are looking for one PhD student to join our team in
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-friendly software tool, based on state-of-the-art machine learning models [1], that can predict the outcome of HFNC therapy in individual patients with higher accuracy than current clinical indices, early in