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measurements are sensitive to the dielectric constant and object geometry. So far, we have used this technology to estimate the vegetation water content (VWC), provide information on the vegetation structure
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enhanced MRI with computer simulations of image contrast and mass spectrometric imaging of tissue samples and single cells. This project is part of the Collaborative Research Centre 1450 “Insight
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to the success of the whole institution. The Faculty of Electrical and Computer Engineering the Institute of Semiconductors and Microsystems together with the German Cancer Research Center site Dresden, Division
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approach for OFR, building further on existing methods; (2) quantify the value of OFR in Luxembourg ; (3) quantify the impact of forest disturbances on the OFR supply and value; (4) estimate the supply and
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like to more widely explore the possibility of computer simulations to refine the targeted synthesis even more and predict the self-assembly even better. Who we are · The Research Training Group RTG2670
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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with
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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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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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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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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