23 machine-learning-phd-in-netherland Fellowship positions at Hong Kong Polytechnic University in Hong Kong
Sort by
Refine Your Search
-
health monitoring, preferably with a publication record in top-tier journals; and (c) be proficient in mainstream research frameworks for deep learning and computer vision. Applicants are invited
-
”. Qualifications Applicants should: (a) have a PhD degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field, and must have no more than five years of post-qualification
-
machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai
-
PhD degree in Computer Science, Linguistics and Communication, Psychology, Social Science, Humanity or a related discipline or an equivalent qualification and must have no more than five years of post
-
preliminary research on the application of brain-computer interface technology in enhancing tourism experiences for families with ASD children”. Qualifications Applicants should have: (a) a doctoral degree
-
and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
-
application; (b) experience in conducting human neuroscience research and/or be proficient in computer programming, e.g. Matlab and Python; (c) a good command of both written and spoken English; and (d
-
the research project - “White adipose tissue (fat) dysfunction in ageing and its related metabolic diseases: new insight and therapeutic intervention”. Qualifications Applicants should have: (a) a PhD degree
-
research using methods such as sensing technique, 3D printing, human-computer interaction, simulation, and/or machine learning to address challenges in machinery motion planning and construction safety
-
or an equivalent qualification. For all posts, applicants should also: (a) have solid experience in electric machines, finite element methods and theory of electromagnetic files; and (b) be able to complete