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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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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
of Education (Ref.: 533113). To commence from as soon as possible to 31 August 2027 Applicants should possess a doctoral or master’s degree in Education, the Learning Sciences or a related discipline, with a
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an outstanding research track record and extensive expertise in cancer bioinformatics, cancer biology, cancer immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with
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immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with cell culture, cellular/molecular biology, and animal studies. The ideal candidate should be self-motivated
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development workshops for teachers and school leaders on STEAM education, artificial intelligence, science education, language education, self-directed learning and innovation leadership; coordinate and liaise
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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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automation—specifically motion planning, path optimization, sensor fusion, or robot learning—ideally with ROS or embedded systems experience; proficient in written and spoken English; good communication
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learn and perform state-of-the-art research for drug target identification and drug development. Enquiries about the duties of the post should be sent to Professor Clive Chung at cyschung@hku.hk
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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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. 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