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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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for our clients from numerous industries. Overarching top topics at Fraunhofer ITWM are Machine Learning as well as Artificial Intelligence and Renewable Energies or Sustainability. In addition, Next
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for our clients from numerous industries. Overarching top topics at Fraunhofer ITWM are Machine Learning as well as Artificial Intelligence and Renewable Energies or Sustainability. In addition, Next
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for our clients from numerous industries. Overarching top topics at Fraunhofer ITWM are Machine Learning as well as Artificial Intelligence and Renewable Energies or Sustainability. In addition, Next
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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-processing, and machine learning textual analysis of the full text of policy documents. Qualitative content thematic analysis is envisioned to compliment structural topic modelling to identify strategies and
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic
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., based on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms