112 engineering-in-image-processing-"MONASH-UNIVERSITY" PhD positions at Nature Careers
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About the FSTM The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
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About the FSTM The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine
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to process and understand large experimental datasets (e.g., image processing) #analyzing experimental results; developing conceptual models and parameterizations #scientific publication and presentation
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About the FSTM The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine
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, or a related discipline. Hands-on research experience in one or more of the following areas will be considered an advantage: Confocal microscopy and Image processing Optical bench instrumentation
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, or related Experience and skills · Multi- and hyperspectral images processing · Knowledge of quantitative remote sensing · Knowledge of physical and statistical modelling concepts
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. For TUD diversity is an essential feature and a
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning