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position of a University assistant (prae doc) as soon as possible, at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science under the supervision of Univ.-Prof. Dipl
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/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning
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Profile Responsibilities Design and implement analysis pipelines for high-throughput microscopy and sequencing data Develop novel image-analysis and machine-learning approaches for quantitative cell biology
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to develop new methods, for example using machine learning. have a proven track record of independent research funding and high quality publications. have at least 5 years of post-PhD work experience
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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to investigate the uterine endometrium and maternal-fetal interface, with the goal of improving female and fetal health. More information about the lab and their work can be found by visiting https
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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of Molecular Biology (LMB), within a programme aimed at studying the neural circuit basis of behaviour. Specifically, to map the synaptic wiring diagram, or connectome, of whole brains, using machine learning