Interested applicants are invited to apply directly at the NUS CareerPortal. Please note your application will only be processed if you apply viaNUS Career Portal.
NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Mathematics%29/32554-en_GB/?st=B4F0BB890E1B2C104B997DC78512E046CAC5DE27
We regret that only shortlisted candidates will be notified.
Job Description
The successful candidate will work with Professor Toh Kim Chuan on methods for convex relaxations of polynomial optimization under a project on "Methods for nonsmooth nonconvex optimization".
The main responsibilities of the position include the followings:
• Conduct independent research on the design, analysis and implementation of efficient and robust algorithms for large-scale structured polynomial optimization problems.
• Conduct simulations and experiments to validate established theoretical results and evaluate the performance of the proposed algorithms.
• Prepare technical reports, research papers, and presentations for academic conferences and journals.
• Work closely with faculty members, postdocs, and PhD students on research projects.
Qualifications / Discipline:
• Graduating PhD or recent PhD holder specializing in computational optimization.
Skills:
• Advanced knowledge on optimization theory and algorithms at PhD level is required, especially strong theoretical and numerical understanding of advanced polynomial optimization algorithms for matrix polynomial optimization
problems.
• Proficiency in Python or Julia, Matlab for algorithmic implementation.
• Good academic writing and presentation skills for publishing research findings.
• Ability to work independently and collaboratively in an interdisciplinary research environment.
Experience:
• At least 2 years of independent research experience in the analysis of convex relaxations for polynomial optimization problems.
• Demonstrated research and intellectual ability, such as having published research papers in premier optimization journals related to the job requirements.