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processing of large data sets, knowledge of data acquisition systems, signal and image processing as well as experience in measuring acoustic pressures in cavitating liquids and high-speed filming is highly
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benefit from the extensive and broad expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and with clinicians at Great Ormond
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(Mechanical Engineering at UCL) will also collaborate, he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect that the PhD
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Neuroimaging, MRC BNDU, and the Oxford Health NIHR BRC. About You You will hold a PhD in biomedical engineering, neuroscience, or a related field, and have experience in the development of technological systems
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biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and clinicians at Great Ormond Street
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 7 days ago
the IMPRS CoNI is English, German language skills are not mandatory. For PhD applicants, a minimum score required for a TOEFL paper-based test is 550. The minimum score for the TOEFL computer-based test is
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resolution microscopy and single molecule imaging. Later in the PhD we will map the transacting proteins and signals required for localising the more interesting of these mRNAs and relate these molecular
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imaging, spatial data analysis, and machine learning. One arm of the project will seek to engineer diverse quantitative features (e.g., adapting concepts and metrics from network science [5] to characterise