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-molecule TIRF microscopy, biochemical reconstitution, and fluorescent labeling, we will watch individual RNA molecules and degradosome complexes at work, capturing millisecond-scale dynamics that shape gene
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projects of other members of the group. - Clear and tidy annotation of the protocols, designs, data and analysis in the ELN indicated by the PI. - Clearly label all material and include it regularly in
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questions in the areas of self-supervised/label-efficient learning and explainability of deep neural networks (XAI) are being developed, particularly for use in biomedical applications. Further information
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molecular labeling through our studies in the synthesis and study of bioactive nitrogen-containing molecules. A PhD in Chemistry or a related field is required. Interested applicants should describe
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highly multidisciplinary environment that spans fundamental discovery through to patient care. Our researchers benefit from outstanding core facilities, including state-of-the-art label-free bioimaging
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++ and CUDA) Code verification and validation of simulations Providing simulation results to project partners and customers Active participation in project, group and lab meetings, knowledge transfer
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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA
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proximity labeling, mass spectrometry and proteomics and experience with cell culture and flow cytometry, preferably working with immune cells. Having your own project, you will team-up with dedicated
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(based on biomaterials and living cells), including their efficient deployment on embedded hardware, as well as the design and management of the supporting data pipeline. You will be part of
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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA