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Field
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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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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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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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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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research is currently the main focus. Here, laboratory experiments are usually combined with state-of-the-art methods such as optogenetics, connectomics or machine learning. Activate map To activate the map
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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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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
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existing technologies, 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
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to environmental cues. Innovation drivers include the development of advanced technologies and the full integration of complex computational approaches to answer relevant biological questions. To learn more about
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research