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learning environment for our students. This position involves a teaching commitment, which may be in the area of hydraulic methods, geodata management, field methods or aquatic geochemistry
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is internationally recognized for its expertise in applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. Under the motto 'Where
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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, machine
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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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desirable. The ability to publish and teach in German and English, as well as in a disciplinary and interdisciplinary manner, is mandatory. If German is not your native language, you must provide proof
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of written and spoken English (other language skills are an advantage) Experience in scientific research and scientific work is an advantage Good computer skills (MS Office) Independent and creative working
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Would you like to gain experience in a modern and professional team and learn firsthand how research and development in the field of computational imaging works? Then you've come to the right place
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public transport or car (including free parking) 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The advertised position is available for 3 years. We look
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of polishing processes for machining reflective optics made of glass and metal for applications in instrumentation for space, astronomy, and lithography Continuous improvement and implementation of processes
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of machine design and the fundamentals of textile technology are an advantage Basic knowledge of programming (e.g., Python or MATLAB) is an advantage You have some experience working with CAD software