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Field
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: Artificial Intelligence – The candidate will contribute to the AI field by researching how different AI solutions coexist with humans in an organizational context and what should be considered in the design of
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for individuals with a strong interest in artificial intelligence, machine learning, process systems engineering, and pharmaceutical manufacturing. The expected outcomes will contribute to more resilient
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of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system including propulsion motors, power converters, fuel cell and batteries etc within the real-time simulation
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you join us? At our Heilbronn branch, we research and develop electronic digital circuits with the aid of artificial intelligence together with our partners from industry and academia. The focus is on
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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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of advanced computational techniques. This research will integrate power system modelling, optimisation algorithms, and artificial intelligence (AI) techniques to develop an innovative framework for strategic
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SpeedGoat. Development of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system including propulsion motors, power converters, fuel cell and batteries etc within
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artificial intelligence (AI) technologies, based on hardware inspired by the structure and function of the brain for superior energy and latency performance in embedded and human-centric applications. We offer
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University of Munich (TUM) , focusing on cutting-edge research in digital health, wearable sensing, and embedded artificial intelligence. The Project title is ‘IoT-based Assisted Living’ and the main purpose
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | about 2 months ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis