Postdoctoral Fellow in Global Health and Big Data
The University of Hong Kong 's highest priorities are to create opportunities for the very best academic talents to excel and to advance human knowledge to the benefit of society. We serve the needs of Hong Kong, the wider region and the rest of the world.
Work type: Full-time
Department: Li Ka Shing Faculty of Medicine (20000)
Categories: Academic-related Staff
Applications are invited for appointment as Post-doctoral Fellow in Global Health and Big Data (several posts) in the Li Ka Shing Faculty of Medicine (Ref.: 500589), to commence as soon as possible for one to three year(s), with the possibility of renewal subject to satisfactory performance.
The selected candidates will work in a company incorporated by the University of Hong Kong that was established to administer and support the University’s innovation endeavors.
Applicants should possess a Ph.D. degree and a strong research background in Epidemiology, Pharmacoepidemiology, Biostatistics, Communicable and Non-communicable Diseases, Antimicrobial Resistance, Genomics, Bioinformatics, Big Data Analytics or Artificial Intelligence Analytics. They should have a good command of written and spoken English, strong communication skills and a demonstrated track record of publishing academic research papers; and also be self-motivated, hardworking and able to work well in an interdisciplinary team.
The appointees are expected to contribute to collaborative research projects on global health, post-marketing surveillance of medicines and precision medicine using artificial intelligence and novel data analytics. Working off-campus may be required.
A competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.
The University only accept online application for the posts. Applicants should apply online and upload an up-to-date C.V. and research publication list. Review of applications will start from July 29, 2020 and continue until October 14, 2020, or until the posts are filled, whichever is earlier.