Precision Prediction Models of COVID-19
A postdoc position is available at the Chan Molecular Epidemiology and Bioinformatics Laboratory (CMEB) in the Department of Biomedical Sciences and the Department of Electrical Engineering at the University. Our laboratory is highly multidisciplinary including public health and engineering. This project will derive the parameters for building the prediction models and use state-of-the-art machine learning, including deep learning techniques, to build analytical engines related to COVID-19. The appointee will combine molecular biology, bioinformatics, biostatistics, and epidemiology to build prediction models for COVID-19 using human medical data.
A PhD degree from an accredited institution and appropriate experience and training in one of the following disciplines: Bioinformatics, Biostatistics, Molecular Epidemiology, Computational Biology, Computer Sciences or Data Engineering with no more than 3 years of experience after the award of a PhD degree.
Highly motivated with demonstrated ability to carry out independent research; experience with prediction model building using machine learning algorithms and data analysis with electronic health records; highly self-driven and innovative with excellent written and spoken communication skills in English; and strong publication record are required. Candidates with experience in processing and/or analysing electronic medical health records are preferred.
(Those who have responded to the previous advertisements need not re-apply.)
Salary offered will be highly competitive, commensurate with qualifications and experience. Fringe benefits include leave, medical and dental consultations at the campus clinic.
Further information on the post and the University is available at http://www.cityu.edu.hk, or from the Human Resources Office, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong [Email : email@example.com/Fax : 2788 1154 or 3442 0311].
City University of Hong Kong is an equal opportunity employer and we are committed to the principle of diversity. Personal data provided by applicants will be used for recruitment and other employment-related purposes.
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