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stimulating environment and gain international exposure through our partners and collaborators across Europe and the world. We support career development, continued education, life-long learning and provide
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim to ensure that all our
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radiation beamline hands-on experience in X?ray microscopy techniques, X?ray diffraction or X?ray fluorescence working knowledge of image processing e.g. using machine learning German skills For further
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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance
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and others) 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
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learning approaches for high-dimensional data, and programming skills in R or Python. Profile Track 2 – Experimental Immunology / Bone Marrow Biology / Trained Immunity Candidates with an experimental
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The Leibniz Institute for Neurobiology (LIN) is an internationally recognized neuroscientific research institute and dedicated to the research on learning and memory. Our research comprises all
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
environment that provides equal opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection