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Magnetic Resonance (NMR), and other biophysical techniques, to investigate the molecular mechanism of RNA function. When function of these molecular machines becomes apparent, it also provides a variety of
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of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and
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experience with machine learning techniques in general and neural networks in particular will be highly beneficial.
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high-throughput stimulus-response experiments and use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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psychiatry. The projects will involve advanced epidemiology, pharmacoepidemiology, and machine learning methods. You will be part of a well-funded and successful research group, collaborating with
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span over the physical, media access control, and network layers. Methods from networking, communication theory, machine learning, signal processing, and optimization will likely play an important role
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and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The tasks include primarily leading and conducting research
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and biology of infection with a strong computational profile. This research subject area aims to lead to innovative development and/or application of novel data-driven methods relying on machine