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Assistant (Doctoral Candidate) with specialising in multimodal imaging (salary scale 13 TV-L, 65 %) The fixed-term position is for a duration of 36 month in accordance with the project duration. Your role In
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-deep knowledge in the applications of Hyperspectral Imaging, Biospeckle Imaging, Laser-Light Backscattering Imaging, LEDs, and Bandpass Filter-Based Imaging techniques Basic knowledge of substrate
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analysis technology3D high-throughput imaging or patient biosample processing Ability to work in a multidisciplinary and international team of scientists with excellent written and oral communication skills
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this research project, state-of-the-art techniques will be employed including multi-spectral imaging, methylome analyses, RNA-Seq at single-cell and bulk levels, cell culture as well as bioinformatics analyses
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) structures using high energy X-ray methods (scattering, spectroscopy, imaging) Design, optimization, and testing/benchmarking of reactors for operando studies Unravelling of relationships between catalyst
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
, JWST, VLT/MUSE and more instruments. Depending on the exact position, candidates with prior experience in handling ALMA, HST and/or JWST imaging data, molecular gas (structure) analysis, (stellar
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with animal models, transcriptomics (long read, single cell), multi-parameter flow cytometry, molecular biology and fluorescence imaging will be preferred. We offer an interdisciplinary research team
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. Experience in working with animal models, transcriptomics (long read, single cell), multi-parameter flow cytometry, molecular biology and fluorescence imaging will be preferred. We offer an interdisciplinary
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efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation
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medical machine learning for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and build their early scientific career. About