236 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Germany
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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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% for PhDs and TV-L E14, 100% for PostDocs; 45k
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics or chemistry, or
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq
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culturing, integrating multiple automated subsystems with image-based machine learning models. Our objective is to enable robotic decision-making through machine learning, paving the way for a standardized
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The Fraunhofer Institute for Molecular Biology and Applied Ecology IME conducts applied life sciences from the molecule to the ecosystem. It is our vision to pave the way to a sustainable future