54 evolution "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" research jobs at THE UNIVERSITY OF HONG KONG
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research team to conduct data analysis for different types of data, including genomic/metagenomic sequencing data, ecological surveillance data, as well as development of analysis pipeline. Working off
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information, please contact Professor Stephanie Ma at stefma@hku.hk . Details of Professor Ma’s research can also be found at http://thesmalab.com/ . Information about the School of Biomedical Sciences can be
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@hku.hk . Details of Professor Ma’s research can also be found at http://thesmalab.com/ . Information about the School of Biomedical Sciences can be obtained at http://www.sbms.hku.hk/ . A highly
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only accepts online application for the above post. Applicants should apply online and upload the following documents at the University’s Careers site (https://jobs.hku.hk ). A thesis abstract (up to 1
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accepts online application for the above post(s). Applicants should apply online at the University’s Careers site (https://jobs.hku.hk ) and upload an up-to-date C.V. They should also arrange 2 referees
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through the University’s careers website (https://jobs.hku.hk ) and upload an up-to-date CV, cover letter (not exceeding 300 words), research proposal (not exceeding 1500 words), and writing sample
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, transcriptomics data, Nanopore long read sequencing analysis and/or multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for
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The University only accepts online applications for the above posts. Applicants should apply online at the University’s careers site (https://jobs.hku.hk ) and upload the following documents: a cover letter; an up
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post(s). Applicants should apply online at the University’s Careers site (https://jobs.hku.hk ) and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities