Sort by
Refine Your Search
-
frameworks (e.g., PyTorch, TensorFlow) and medical image processing is essential. Candidates should demonstrate a track record of peer-reviewed publications in the field of AI for medical imaging. Preference
-
for appointment as Senior Research Assistant. Research experience in organoid research would be advantageous. Candidates should be highly motivated and demonstrate a keen interest in microbiology research. A track
-
. Previous work experience in big data analysis, managing large databases of research projects relating to family caregivers of older adults and/or cost effectiveness evaluation, and with related track records
-
qualitative tools. Previous involvement in research studies in GPS and GIS technology is highly preferred. Track record of scholarly output. High proficiency in written and spoken English and Chinese (including
-
Bachelor’s degree or above preferably in education field, with at least 3 years’ extensive experience in educational research and large-scale studies including project management and coordination, tracking
-
to administrative duties as required. Enquiries about the post should be sent to Professor Hongjie Dai at hjdai@hku.hk . Those with relevant post-doctoral work experience or an excellent publication track record may
-
a collaborative team environment. Essential Skills and Experience: Strong expertise in molecular biology and cancer biology, with a proven track record in these areas. Substantial experience in animal
-
; (iv) proven track records and ability to work independently and within a team; (v) keen interest in research work in the field of ophthalmology and visual sciences; and (vi) self-motivation, sincerity
-
analysis, R language or related statistic software, or/and Python software, or programming skills of deep learning tools; (iv) proven track records and ability to work independently and within a team; (v
-
. Those with relevant post-doctoral work experience or an excellent publication track record may be considered for appointment as RAP. The appointee will join the Quantitative History Cluster led by