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position that can be applied across a broad range of industrial sectors, bringing the benefits of passive linear optical superresolution to the domain of in-process control for additive manufacturing
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Ref NumberB02-08605Professional ExpertiseClinicalDepartmentSchool of Life & Medical Sciences (B02)LocationLondonWorking PatternFull timeSalarySee advert textContract TypePermanentWorking TypeOn
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parasite biology and access to facilities including a derogated CL3, and state-of-the-art flow cytometry, genomics and imaging facilities. Applicants with enthusiasm for teaching at undergraduate and
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passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
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(https://www.cam.ac.uk/research/research-at-cambridge/strategic-research-initiatives-networks ). The School of Biological Sciences has state of the art facilities in imaging, high performance computing and
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KEK, QUP Position ID: KEK -QUP -POSTDOC19 [#30165, KEK-QUP-PD2025-1] Position Title: Position Location: Tsukuba, Ibaraki 305-0801, Japan [map ] Subject Areas: Data Science / Machine Learning
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within the group and across Research & Development. Who You Are: PhD in Computational Biology, Computer Science, Applied Mathematics, or similar field Demonstrated record of innovative scientific
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. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated postdoctoral fellow to develop cutting-edge methodologies in computer vision and AI to power whole slide image
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Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge in signal representation/processing, data-driven and machine learning/analysis, esp in climate related topics. Prior
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and skill in programming with MATLAB or Python. Research experience in MEG, in vivo electrophysiology, in vivo two-photon/miniscope imaging, slice electrophysiology, and mouse brain surgery is desired