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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 533004 Work type: Full-time Department: School of Biomedical Sciences
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proficient in data analysis using statistical or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic
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Kong Application Deadline 31 Dec 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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) Country Hong Kong Application Deadline 18 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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Application Deadline 30 Sep 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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. Applicant(s) should possess a Ph.D. degree, or equivalent, in biological or computer sciences or a related discipline. Experience in any of the following fields, including 1) biological image acquisition
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forefront of academic scholarship for many years. The University has a comprehensive range of study programmes and research disciplines spread across 10 faculties and over 140 academic departments and
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, Marine Science, Computer Science, or related fields (obtained within the last 2 years). Strong research record with publications. Experience in programming, satellite data processing, and/or fieldwork
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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-performance computing (HPC) environments and large-scale numerical codes for space plasmas; proficiency with scientific programming (e.g., Fortran/C/C++/Python) and Linux is an advantage Experience with data