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Field
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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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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strong background in biological sciences who are enthusiastic about contributing to cutting-edge research. The Cao Laboratory utilizes and develops cutting-edge single cell omics, genetic, imaging and
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molecular biology, quantitative imaging and biophysical approaches to investigate cell shape changes in cultured cells and in vivo. Current projects in the lab include investigating the regulation
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at the intersection of machine learning, bioinformatics, and computational pathology. Project Overview: Integrating histopathological imaging with omics (e.g., transcriptomics, genomics, proteomics) holds tremendous
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particular focus will be on preparing and testing new imaging protocols for brain tumors, where the technology is evaluated for clinical application. The work is carried out in close collaboration with
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mechanisms underlying psychosis. The research utilizes advanced multiphoton imaging and virtual reality platform for simultaneous recording of animal behaviour and microcircuit activity. RESPONSIBILITIES
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis
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industrially-relevant human-made materials. This project will address key priorities in the microscopy sector by developing workflows that integrate cutting-edge imaging and characterization techniques and