21 parallel-processing "LCC CNRS" Postdoctoral positions at THE UNIVERSITY OF HONG KONG in Hong Kong
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the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 537011 Work type: Full-time Department: Department of Electrical and Computer Engineering (14300
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Ref.: 537011 Work type: Full-time Department: Department of Electrical and Computer Engineering (14300) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Applications
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record demonstrating expertise in multi-omics analysis, particularly single-cell and spatial transcriptomics. This includes the processing and interpretation of multi-omics, single-cell (e.g., scRNA-seq
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adolescents, supervision of research interns, data processing, and other research-related duties as assigned. A highly competitive salary commensurate with qualifications and experience will be offered, in
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assigned Requirements A Ph.D. degree in Neuroimaging, Biomedical Engineering, Electrical Engineering, Physics, Computer Science, or other related disciplines, with experience or keen interest in processing
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experience. Applicants who are in the process of completing a Ph.D. degree will also be considered. Desirable qualifications include physics deep learning, digital twin, smart and resilient infrastructure
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: Collecting, cleaning, and analysing research data under supervision, ensuring accuracy, quality and integrity throughout the process. Preparing comprehensive technical reports detailing research methods
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of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R. They should
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throughout the process. Preparing comprehensive technical reports detailing research methods, findings, and implications. Developing manuscripts for submission to high-impact academic journals and presenting
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images