Research Fellow, Computational Optimization in Python
The successful candidates will work with Prof. Shoemaker and her group to develop, implement and/or evaluate serial and parallel single or multi objective optimization algorithms for black-box objective functions.
The optimization problem can be expected to have multiple local minima/maxima. Surrogate methods are considered also since computational efficiency for computationally expensive objectives (e.g. simulations) is greatly enhanced with them.
- PhD in Operations Research, Industrial Systems Engineering, Applied Mathematics, Computer Science or related field.
- Experience in developing complex computer codes in Python.
- Prior knowledge of surrogate global optimization is an advantage.
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 presences are required.
In accordance with Singapore's legal requirements, unvaccinated workers will not be able to work on the NUS premises with effect from 15 January 2022. As such, job applicants will need to be fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Industrial Systems Engineering and Management
Employee Referral Eligible: No
Job requisition ID : 14029