Research Fellow, Industrial Systems Engineering And Management
Applications are requested for Research Fellow (Postdoc) positions on computational surrogate optimization (deterministic and/or stochastic) with Prof. Christine Shoemaker, Distinguished Professor in the Department of Industrial and Systems Engineering at the National University of Singapore (NUS).
It is an advantage, but not a requirement for a candidate to have expertise in any of the following areas: surrogates (including RBF or GP/BO), distributed (parallel) computing, algorithm proofs, machine learning, uncertainty quantification, statistics, numerical analysis). If candidate has prior optimization (e.g. nonlinear programming) experience, prior knowledge of surrogate global optimization is not required.
Research Focus and Goals
The successful candidates will work with Prof. Shoemaker’s group (which is a mixture of OR/ISE and Statistics postdocs & PhD students) and possibly other NUS faculty to develop serial and parallel optimization algorithms for simulation models and/or apply the algorithms to complex engineering problems. The optimization model can be expected to have multiple local minima/maxima. Computational efficiency is greatly enhanced with Surrogate algorithms. Surrogate optimization has been coupled with machine learning to solve complex problems e.g. see  below. The candidate will have the opportunity to develop research skills, improve domain knowledge and expertise, attend international conferences, and work on a Supercomputer.
The initial term of appointment for Research Fellows can be up to 30 June 2021. (And shorter term terms are possible.) The remuneration and benefits are internationally competitive http://www.nus.edu.sg/careers/whatyougettoenjoy.html
Job applications and inquiries should be sent to Prof. Shoemaker at firstname.lastname@example.org. Applicants should include a CV and indicate desired start time. Please also put “Job Application 2019 opt” in the email subject line. Review of applications will begin immediately and continue until the positions are filled. Candidates will be considered who would like to start as soon as possible as well as those who cannot begin for many months.
Professor Shoemaker (PhD in mathematics, member of the USA National Academy of Engineering and Fellow in the following societies: SIAM, INFORMS, AGU, ASCE) was Ripley Professor at Cornell University in USA before coming to NUS. She is co-author (with Dr. David Eriksson and Prof. David Bindel)) of open source surrogate global optimization toolbox “pySOT” in GitHub (which has had over 88,000 downloads). This toolbox provides codes for Prof. Shoemaker‘s multiple RBF algorithms developed over a decade and for GP methods, and makes it easy for users to modify the algorithms). More information at https://sites.google.com/site/shoemakernusgroup/home  Ilija Ilievski, Taimoor Akhtar, Jiashi Feng, and Christine Shoemaker. Efficient hyperparameter optimization of deep learning algorithms using deterministic RBF surrogates. In 31st AAAI Conference on Artificial Intelligence (AAAI-17), 2017.
- A PhD in Operations Research, Industrial/Systems Engineering, Applied Mathematics, Computer Science or from similar programs. Position is also available to those close to receiving PhD.
- Extensive experience in developing complex computer codes, e.g. in Python or C++.
- Ability to construct and write papers for leading research journals and conferences.
Location: Kent Ridge Campus
Department : Industrial Systems Engineering And Management