76 postdoctoral-image-processing-in-computer-science PhD positions at Technical University of Munich in Germany
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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research experience and are explicitly encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by integration into TUM’s School of Life Sciences or School of Management and
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science, physical chemistry, materials science, or materials engineering, or a closely related field • Experience with cellulose and its processing technologies is an advantage • Strong willingness
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-established and highly visible track record of the laboratory in the analysis of plant growth processes regulated by AGC1 kinases. The Chair of Plant Systems Biology has strong expertise in all relevant
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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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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Risk Analysis Group at TUM and Prof. Maria Pina Limongelli at Politecnico di Milano, offering an excellent international research environment. About us The Engineering Risk Analysis Group at TUM
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processes regulated by AGC1 kinases. The Chair of Plant Systems Biology has strong expertise in all relevant molecular, cell biological, biochemical, physiological and genetic techniques. The group also has
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(MCQST) is inviting applications for a Ph.D. or postdoctoral position. In recent years, spin defects in diamonds have been shown to act as atomic-sized sensors for nanoscale- microscopic magnetic field