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Field
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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external forcings on climate analysis of climate model output by means of classical statistical and machine-learning methods coordination of scientific workflows among project partners Your profile Master's
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, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines Language requirements English C1 or equivalent Application deadline January, please see website for exact
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Fraunhofer MEVIS is a world leading and internationally connencted research center for computer assistance in medicine. With about 140 employees, our mission is to conduct patient-centric research
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applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. At the headquarters, on the campus of “Technische Universität Ilmenau
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areas best match your interests. You would like to learn more about our institute? Get to know the Fraunhofer ITWM and gain insights into our Institute. (youtube.com) What you will do At our institute
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diploma or master’s degree specializing in Automation Engineering, Computer Engineering, Control Engineering, or Electrical Engineering. You already have knowledge in the field of automation engineering
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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Machine learning Experience is ideally shown through a thesis, seminar papers, or scientific publications. Alternatively, excellent grades in a respective Master’s programme. Strong intrinsic motivation
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research areas. New insights and synergetic effects resulting from collaboration between inherently different viewpoints of separate fields typically accompany this endeavour. Our task force on machine