Research Assistant, Simulation Modelling and Bayesian Optimization

Job Description

We have an opening position for a Research Assistant  in the area of simulation modelling and optimization. The emphasis will be on metamodeling for computer simulations and algorithmic development for simulation optimization. Knowledge of Gaussian Process (GP) models and Bayesian Optimization (BO) would be an advantage, but not a requirement.  Experience with high dimensional data and machine learning techniques would also be a plus.

We are considering applicants with strong analytical skills and programming knowledge.

Job Requirements

Candidates applying for this position must possess a degree in  Industrial Engineering, Statistics and Mathematics or a related science or engineering discipline.

• Background in analytical modeling, applied statistics and applied probability.
• Good programming skills in Python, C++, MATLAB.

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 : Industrial Systems Engineering and Management
Employee Referral Eligible: No
Job requisition ID : 18772