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of computer science or using computer vision methods Excellent knowledge of the development and implementation of methods in the field of digitization, artificial intelligence, machine learning and/or 2D/3D imaging and
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental parameter measures and DNA data. Your Tasks Participation in fieldwork in Germany
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collaborate closely with a dedicated team of soil fauna experts, ecological data modelers, computer-vision system engineers. Your Tasks Establish data science pipelines, data-modelling strategies, model
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. Given this, the CUI: Advanced Imaging of Matter Graduate School features an interdisciplinary research and training programme for doctoral students and post-doctoral researchers. It is addressed to young
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and the willingness to work in a team are expected. Our offer Work in a dynamic, international and interdisciplinary environment Close cooperation with computer scientists of the Research Group Data
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and IT develop innovative radiopharmaceuticals and novel tools for functional characterization, improved imaging and personalized treatment of tumors. The Department of Department Life Science
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 2 months ago
Scientific university degree in neuroscience, psychology, biomedicine, computer science or a related field Experience with imaging procedures (e.g. MRI, fMRI pre-processing) Thorough knowledge of data
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data to modeling in digital representations to the final visualization and human-machine interaction. We develop modern AI solutions in the areas of 2D/3D image and video understanding, computer vision
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this knowledge gap and establish improved GHG models accounting for soil invertebrates. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental