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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
Researcher (R3) Country Hong Kong Application Deadline 21 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
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Recognised Researcher (R2) First Stage Researcher (R1) Established Researcher (R3) Country Hong Kong Application Deadline 31 Oct 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job
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Experience in image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed
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(R2) Established Researcher (R3) Country Hong Kong Application Deadline 30 Nov 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework
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Researcher (R3) Country Hong Kong 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
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to structural biology, protein engineering, machine learning, molecular cloning, in vivo experiments, and/or CRISPR technology. Candidates must exhibit a strong command of written and spoken English, and
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
Applicants should possess a doctoral or master’s degree in Education, the Learning Sciences or a related discipline, with a strong background in technology-enhanced learning and assessment, learning design and
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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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. Knowledge and skills in mathematics, biostatistics, or advanced statistical techniques in clinical research, database management, and machine learning (AI) will be taken into account. They should have
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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