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of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation
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combined with soil sensors systems and UAVs with multispectral cameras. Your tasks in detail: Development and application of high resolution time-lapse GPR and EMI imaging methods at multiple scales
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) theoretical and practical experience in peptide chemistry, nucleic acid chemistry as well as knowledge of bioassays are beneficial Experience and knowledge in fluorescence spectroscopy/imaging is desired
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regulatory networks, cell behaviour, and morphology during this process. By examining species across evolutionary scales, we aim to uncover the mechanisms underlying morphological evolution and the general
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Purkinje cells affects information processing in the thalamo-cortical network. Perform experiments in cerebellar organotypic slice cultures using GCaMP6-based calcium imaging and chemogenetics. Perform
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. However, the transcriptional regulation of this process remains is not fully understood due to the complexity of crop plants as models for molecular and imaging studies. This DFG-supported project aims
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) on Foundation Models and/or Deep Learning for Imaging Problems. The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing. The current focus is
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location in Dortmund, we invite applications for a PhD Candidate (m/f/d): Mass Spectrometry Imaging The position is to be filled within the framework of the EU-funded project European doctorial network
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causative treatment in the patients. Work will employ genetic tools, manual and automated patch-clamp measurements, immunohistochemistry, confocal/STED imaging, light-sheet fluorescence microscopy, and
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inviting applications for a PhD Student (f/m/x) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project description Single molecule X-ray