Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole
-
in probability, stochastic analysis, and optimization. Applicants with knowledge in machine learning, as well as a track record of publications in top Actuarial Science, Mathematical Finance
-
, or a related field. Candidates must possess relevant research experience in probability, stochastic analysis, and optimization. Applicants with knowledge in machine learning, as well as a track record
-
demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
-
to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected
-
machine learning and operations research. b) The applicants are expected to deliver research outcomes to our industry partners, to support practical applications in semiconductor manufacturing. c
-
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 to ample
-
(machine learning, computational modeling, digital health etc.) Interfacing Engineering with Clinical Medicine (linking biomedical, mechanical, and electrical engineering together with clinical disciplines
-
. 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
-
.) Fundamental Biology & Chemistry (molecular biology, biomaterials, tissue engineering); Artificial intelligence & Data Science related to biomedicine (machine learning, computational modeling, digital health etc