Sort by
Refine Your Search
-
Division of Physics and Applied Physics (PAP) in School of Physical and Mathematical Sciences (SPMS) is looking for a candidate to join them as a Research Assistant. The College of Science seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome...
-
Science, Mathematics, Statistics, or relevant fields. Strong background in machine learning. Experience in machine learning for optimization is preferable. Knowledge with machine and deep learning software packages
-
of individual level data on internships and graduate employment. Compiling, processing, and analyzing data using statistics and econometrics software such as STATA and R. Preparing sections of analysis, writing
-
statistics and quantitative methods, and draw insights based on the analysis presented in a visualized format Assist with College Research Office (CRO) grant workshops and research events Provide support for
-
. Experiences in AI and data analysis are essential. Entry Level candidates are welcome if their PhD theses are in the field. Strong background in machine learning, statistics, and computational modeling
-
in future cyclone risk in the Asia Pacific and apply novel statistical techniques to enable policymakers and planners to understand plausible worst-case scenarios with rising sea-level and changing
-
with the research design and statistical analyses Assist with writing progress and final research reports Contribute to research publications and presentations Engage in the dissemination of research
-
following fields: Large random matrices Machine Learning Job Requirements: PhD degree in statistics or related areas. Experience in random matrices or machine learning Strong written and verbal communication
-
on analysing data using statistical and data science techniques Leading on writing reports, presentations, and publication of results and findings in peer-reviewed journal Generating research questions
-
projection statistical models and interpretation of the results on a range of temporal (historical to future) and spatial (global to regional and local) scales. They will work collectively within a multi