Research Fellow, Deep Generative Models

Job Description

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

• Hold PhD in Transportation, Statistics, or related disciplines
• Has experience of developing and training new deep generative models
• Has good understanding of statistics behind deep learning.
• Is proficient in programming in Python.
• Open to fixed term contract

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Civil and Environmental Engineering
Employee Referral Eligible: No
Job requisition ID : 18014