Research Fellow (Operations Research)

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-%28Operations-Research%29/32541-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

• Conduct literature review on recent research on resource allocation.
• Weekly discussions with the supervisor (myself) on formulating important and novel research problems and brainstorming different approaches.
• Construct mathematical models that capture meaning problem formulations, and identify why existing methods are insufficient.
• Develop solutions in the form of algorithm design and analysis. The analysis involves mathematical proofs and empirical evaluations (require writing codes) on the proposed algorithms and existing benchmarks.
• Prepare slides and present scientific findings in research conferences.
• Writing research papers for submission(s) to top Operations Research (OR) journals, such as NFORMS Operations Research and/or Management Science journals, and/or the MSOM journal.
• May need to work with external collaborators on numerical experiments with real world data (but this job is purely on academic research and is not part of an industrial collaboration project).

Job Requirements

• A strong foundation in mathematics, particularly in probability and optimization.
• A PhD degree (or close to PhD completion) in engineering or management science degree, related to Operations Research.
• The ability in conducting academic research in Operations Research (OR), with skillsets including understanding research papers published in the INFORMS Operations Research and/or Management Science journals, and/or the MSOM journal. The candidate should be able to understand the model, the algorithm(s), the main results and the proofs in a paper.
• Experiences with submitting (new manuscripts and/or revisions) to the top OR journal listed above.
• Proficiency in Python, particularly in optimization package usage and data-analytic related tasks.
• Proficiency in scientific writing, towards to OR research community.
• Willingness to learn new knowledge on resource allocation and data-driven optimization, particularly in the latest development.
• Communication skill, particularly the ability in articulating and discussing scientific ideas, and in presenting scientific findings in research conferences
• The ability to cooperate with other people.
• An interest in exploration academic career in OR.