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Field
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
, the candidate will contribute to other neuroimaging research including novel MRI sequence and imaging marker development to explore the physiological and pathological processes involved in primary and
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for developing novel diagnostic, imaging, and therapeutic strategies. Our program uses peptide- and antibody-based combinatorial library selection to discover, validate, and exploit the vascular biochemical
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
research assignments related to energy conversion systems including: Prototype development Material synthesis and analysis Performance testing Analysis of results Preparing research publications Prepare
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for high-dimensional dependent data, and data sketching approaches for massive data. Opportunities to Contribute: Develop statistical/machine learning methodology for multi-modal imaging data integration
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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Hospital site in Oxford – a friendly, welcoming place of work with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research
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or medical imaging. - Technical Skills: Proficiency in programming languages such as LLMs, CNN, DNN, Python, MATLAB, or R, with experience in imaging software and AI frameworks is desired. - Research Acumen
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, scientific, and regulatory steps required to translate in vitro molecular hits into small animal preclinical evaluation models. Processing and integrating complex transcriptomic, proteomic, and image-based
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statistical modelling, medical imaging data analysis, cancer omics, precision medicine and translational statistics. Depending on their profile, the successful candidate will work on one of the following