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in solar energy by exploring fundamentally the controversy regarding the abnormal evaporation rate and simulate/ predict vapor production rate to guide the design of an optimized interfacial evaporator
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/d) in Energy Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research
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right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning, and computer vision. The main focus is on semiconductor
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to the table You are studying physics, engineering (micro/nanotechnology), chemistry or an equivalent degree program. You are an enrolled student in Chemnitz, Mittweida or the surrounding area. You already have
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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in the chip design process Optimization and Reinforcement Learning methods for problems of design/layout Exploration of Heuristics and Data-driven Methods for the generation of design blocks Automated
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to the answer to this question is an intelligent, central control unit that orchestrates future autonomous vehicle fleets, optimizes road traffic, clears the road in the event of a disaster, switches traffic
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The Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB develops and optimizes processes, technologies, and products for health, sustainable chemistry and the environment
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Autonomous Challenge or EDGAR . Thereby, we research current problem fields in the areas of perception, planning, control, safety and evaluation. Our goal is always to develop the optimal overall software
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for various technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to