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national university of singapore

Research Fellow (Mathematics)

2-4 Years
SGD 5,750 - 11,000 per month
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  • Posted 2 days ago
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Early Applicant

Job Description

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Mathematics%29/32475-en_GB/st=9A4A78DB0823DB4BA251A11A058E4A86FD0CCB50

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 nonsmooth nonconvex 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 convex/nonconvex 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 nonsmooth and/or nonconvex optimization algorithms for matrix and discrete optimizations.
. Proficiency in Python or Julia, Matlab, C++ 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 design and implementation of efficient algorithms for solving large-scale convex/nonconvex nonsmooth optimization problems.
. Demonstrated research and intellectual ability, such as having published research papers in premier optimization journals related to the job requirements.

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Job ID: 145825897

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