Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
Epidemiology or a related field, with substantial experience in dietary analysis, epidemiologic study design, big data handling, and dietary pattern deduction. They must demonstrate proven expertise in
-
The appointees will assist the project leader in the research project - “Uncovering the dynamical landscape of shipping networks through big data analytics”. Qualifications Applicants for the Project Associate
-
federated computation for large-scale data collaboration” for sensitive data collaboration, especially in financial and business data scenarios. He/She will be required to: (a) conduct literature review
-
) [Appointment period: each for two to twelve months] Duties The appointees will assist the project leader in the project - “A large model based data agent for data science and artificial intelligence education
-
or more of the following areas: natural language processing, multimodal learning, large language models, knowledge graphs, graph learning or data mining; (c) be proficient in Python and deep learning
-
accounting, and related areas Big Data and Data Analytics – including big data, business analytics, data visualization, databases, programming for data analysis, and related areas Quantitative Methods
-
a Ph.D. degree in Health Science, Public Health or Geriatric Science, preferably with experience in health service research, advanced data analytics, digital health innovation, and/or big data
-
duties as assigned. Qualifications Applicants should have: (a) an honours degree in Information Engineering or a related discipline or an equivalent qualification; (b) experience in digital forensics
-
; familiarity with time series analysis and complex survey design and weighting is preferred. Experience in epidemiological data analysis of large datasets using R and/or STATA is highly preferred, competency in
-
develop a body of high-quality publications in scholarly journals with global impact Proficiency in statistical software packages, including SPSS and R, for large and complex data analysis Proven knowledge