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collaboratively Meritorious qualifications: Experience with machine learning or deep learning Experience with computer vision or image analysis Experience with 3D data, geometric representations, or parametric
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) geometry and computer vision (including analysis of video, audio, radio, and radar signals), (ii) medical image analysis, and (iii) machine learning and artificial intelligence. The group has extensive
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analysis components and is part of a collaborative effort within the PEPR Cell-ID network. The successful candidate will be responsible for: ● Designing and implementing chromatin tracing experiments (Hi-M
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Biol. 2023;435:167951. https://hal.science/hal-03929029 [2] Valimehr S (AUS), Vuillemot R (FR), Kazemi M (AUS), Jonic S (FR), Rouiller I (AUS). Analysis of the Conformational Landscape of the N-Domains
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project at the forefront of microscopy and bioimage analysis (https://www.msca-agile.eu/ ) and contribute to OMERO integration and optimization of Biom3d, a cutting-edge deep-learning framework for 3D image
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. This part of the project will provide the student with the opportunity to develop analysis tools for 3D experiments that we will use in the final part of the PhD, and also provide us with both concrete
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concepts and communicate them to clients in 2D and 3D Proficiency in user research methods, usability testing protocols, risk analysis tools, and rapid prototyping. Mastery of Stratasys Polyjet J850 and FDM
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cells and the microenvironment; analysis of the role of extracellular vesicles in intercellular communication and modulation of the tumor microenvironment; development of novel therapeutic strategies
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TLDR: Build AI methods for 3D particle detection and structural analysis in cryo-electron tomography data, applied to chromatin organization and synaptic molecular targets. Please include a cover
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executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational structural biology projects are especially relevant. Discuss results, limitations