Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
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
-
Matter Physics / cond-mat-th , Condensed Matter Physics, Electronic Structure, Strongly Correlated Materials , Condensed Matter Theory , Strongly Correlated Materials , Superfluidity and superconductivity
-
-of-the-art techniques to assess the physicochemical properties of nanoparticles, ensuring their stability, drug release kinetics, encapsulation efficiency and electron microscopy imaging. Integrate innovative
-
Avenue, Kowloon Tong, Hong Kong [Email : hrojob@cityu.edu.hk/Fax : 2788 1154 or 3442 0311]. To apply, please submit an online application at https://jobs.cityu.edu.hk. ; Applications will receive full
-
communication skills and strong critical thinking ability; and Ability to prioritise and work collaboratively in a diverse workforce. Please address informal inquiries to Prof Thomas Knopfel via email tknopfel
-
. Qilei CHEN at chenql@hkbu.edu.hk . The subject of the email should be: Application-Personal Name-Position Applicable. The initial appointment will be offered on a fixed-term contract of up to 1 year. Re
-
Investigator: Dr. Zhou Jiajia at email: jiajia_zhou@hkbu.edu.hk . The initial appointment will be offered on a contract of one year. Re-appointment thereafter will be subject to mutual agreement and funding
-
related to social network analysis. For the project information and job inquiries, please contact the Principal Investigator: Dr. Zhou Jiajia at email: jiajia_zhou@hkbu.edu.hk . The initial appointment will
-
Artificial Intelligence (DSAI) is a multi-disciplinary department hosted under the Faculty of Computer and Mathematical Sciences established on 1 January 2025. DSAI will be at the forefront of cutting-edge
-
multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities