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Field
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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protocols, develop machine-learning methods for decision-making, and validate results on lab testbeds. Collaborating with experts in cybersecurity and computer science, the researcher will publish high
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, strongly motivated researcher with knowledge of MR physics. Working knowledge of computer languages (e.g. Matlab) and statistical analysis software for imaging processing of structural and functional MRI
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schedules of participant families Mentorship and Laboratory Responsibilities (10%) Undergraduate mentorship (data entry, coding projects, image processing) Collaborate with a diverse team of researchers
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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, 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 positions (TV-L E13, 100
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, machine learning) Advanced skills in 2D/3D/4D image parsing, segmentation, and building robust computer-aided detection systems Proficiency with modern deep learning frameworks (PyTorch, TensorFlow) and
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of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We are looking for a Post
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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 learning
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). Experience applying machine learning or AI methods in these fields is an advantage. The ideal candidate should also be comfortable structuring, linking, and analyzing large datasets that include dense