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innovative and interdisciplinary scientific network. Scientifically, artificial molecular machine research and technologies are critical fields with the potential to offer significant benefits to chemical
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innovative and interdisciplinary scientific network. Scientifically, artificial molecular machine research and technologies are critical fields with the potential to offer significant benefits to chemical
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modeling (machine learning). We collaborate closely with research institutions and industry partners within and outside Europe. As part of a BMWK-funded research project on climate-neutral aviation
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industries. Overarching top topics at Fraunhofer ITWM are Machine Learning as well as Artificial Intelligence and Renewable Energies or Sustainability. In addition, next generation computing and quantum
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into account various parameters. To this end, a concept is developed, various mathematical models and Machine Learning algorithms are selected and then tested and evaluated within a company environment. What you
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efficient energy and load management strategies using state-of-the-art methods from the fields of predictive control and optimization processes as well as machine learning. The focus is always
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methods and resources at the highest level and advance the IOM's strategic goals. Experience in the field of artificial intelligence (machine learning etc.) is advantageous, a focus on artificial
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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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or a comparable course of study Good Python and/or Java programming skills Machine learning knowledge and experience Experience with Static Analysis is recommended Good language skills in German and/or
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bioinformatics and machine learning, we are offering a position for a highly motivated postdoctoral fellow with significant experience in bioinformatics, ideally in the field of cancer research. The position is