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: What are efficient machine learning strategies to identify large ensembles of nanoparticles in tomograms (i.e., to identify nanoparticles on irregular 2D surfaces in 3D space)? What are appropriate
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Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A
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consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
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, and high-performance computing. About the division and department With more than 30 faculty members, more than 100 PhD students, and more than 300 employees, the Department of Microtechnology and
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-from-motion, and object recognition. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as
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for molecular dynamics (MD), slashing computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with
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collaboration with Lund University. The candidate is expected to have a strong mathematical background particularly in stochastic modeling, optimization, and reinforcement learning. As a PhD student, you devote
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data. Much focus is on large scale analysis based on machine learning, deep learning/AI, as well as handling and analyzing large 3D microscopy data. You will work with shorter and longer projects and
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PhD students, and more than 300 employees, the Department of Microtechnology and Nanoscience also includes one of the largest cleanrooms in European academia. The Microwave Electronics Laboratory
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experimental platform and combine it with continuum modeling of complex materials and machine-learning-based analysis methods to understand and predict biofilm structure and growth. Supervision: Shervin Bagheri