Research Fellow, Industrial Systems Engineering And Management
Applications requested for Research Fellow position for developing/improving computational surrogate optimization algorithms & software working with Prof. Christine Shoemaker, Distinguished Professor in the Department of Industrial & 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: optimization, surrogates (including RBF or GP/BO), distributed (parallel) computing, machine learning, statistics, algorithm proofs, numerical analysis.
Research Focus and Goals
The successful candidates will work with Prof. Shoemaker’s 10-person group (which is a mixture of OR/ISE & Statistics, postdocs & PHD students) and possibly other NUS faculty to develop algorithms, codes and software for serial and parallel optimization algorithms for simulation models and/or apply the algorithms to complex engineering problems and help improve PYSOT software. The algorithms focus on global optimization, i.e. the objective function (e.g. simulation model) can be expected to have multiple local minima/maxima. Computational efficiency is greatly enhanced with Surrogate algorithms including when coupled with machine learning to solve complex problems e.g. see  below. A masters level person in this position will gain extensive experience in programming and software, working with the PYSOT code discussed below. A research fellow in this position will also have the opportunity to develop research skills, publish research papers, attend conferences and deepen knowledge.
The remuneration and benefits are related to highest academic degree and 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 2020 softw” 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).  Ilija Ilievski, Taimoor Akhtar, Jiashi Feng, and Christine Shoemaker. Efficient hyperparameter optimization of deep learning algorithms using deterministic RBF surrogates. In 31st AAAIConference on Artificial Intelligence (AAAI-17), 2017.
- Demonstrated excellence in python programming and in maintaining complex programs.
- Academic background in computer science, or in computational discipline like engineering.
- For PhDs seeking a postdoc (research fellow) position, the candidate should demonstrate ability to construct and write papers for leading research journals and conferences.
Location: Kent Ridge Campus
Department : Industrial Systems Engineering And Management