The candidate will work developing new deep generating models to generate synthetic population and its activity patterns while accounting for social network effects. It will require fusing datasets with different spatial and temporal resolution, such as household travel survey, call detail record, and transit smart card data.
A strong background in probability theory, model-based machine learning, statistics, big-data processing pipelines, high-dimensional data analysis, and discrete choice models would be required to accomplish this work.
The successful applicant is expected to pursue independent as well as collaborative research, must be willing participate in writing grant proposals and in the supervision of doctoral/postgraduate research students.
Job Requisitions
The candidate should
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