Singapore University of Technology and Design, Engineering Systems and Design (ESD)

Position ID: 866-POSTDOCTORALRESEARCHFELLOW [#17202]
Position Title: Postdoctoral Research Fellow (Stochastic Modeling, Operations Research)
Position Type: Postdoctoral
Position Location: Singapore, Singapore 487372, Singapore [map] sort by distance
Subject Areas: Operations Research, Applied Probability, Optimization, Machine Learning, Stochastic Modeling, Statistics, Data Science
Application Deadline: 2021/03/15 11:59PMhelp popup finished (2021/01/21, finished 2021/09/18, listed until 2021/03/31)
Position Description:    

*** this position has been closed and new applications are no longer accepted. ***

Postdoctoral Research Fellow (Stochastic Modeling, Operations Research)

We invite applications for a postdoctoral fellow position to work in the interface of operations research and machine learning in Singapore University of Technology and Design (SUTD). SUTD is established to advance knowledge and nurture technically-grounded leaders and innovators to serve societal needs, with a focus on Design, through an integrated multi-disciplinary curriculum and multi-disciplinary research. It is one of the six autonomous universities in Singapore.

The post-doctoral researcher will be specifically working on developing data-driven models and methods for tackling tail risks in large-scale decision problems affected by uncertainty.

With rapid technological progresses in data acquisition and seamless computation in cloud, data-driven formulations involving large-scale optimization models have become critical for businesses to proactively manage risk and derive value from various analytics endeavours. However, the mere nature of applications we aim to tackle with these large-scale optimization models (think of automated rebalancing of large portfolios, managing omnichannel supply-chains, autonomous vehicles, power distribution networks, etc.) demand that the decisions derived from these automated models are robust, reliable and are not prone to extreme risks due to the presence of uncertainty. Moreover, with modern datasets containing heterogenous subpopulations, it is natural that fairness-critical settings ranging from smart-cities, healthcare, public-transportation, etc. require uniform performance such that no subpopulation of a specified size in the dataset suffers extreme risks. Motivated by these challenges, the research will focus on developing data-driven optimization modeling paradigm for deriving efficient decision choices which possess controlled low probabilities for resulting in extreme risks.

An ideal candidate will have a PhD with expertise in Operations Research background, which naturally includes training in applied probability and optimization models. Applications from candidates with expertise in applied probability, statistical machine learning, statistics, and engineering disciplines which require training in stochastic modeling and optimization are also welcome. Proficiency in programming/scripting and training large-scale machine learning models is an added advantage. 

Applicants should include a cover letter describing their background, and a CV with specifics on academic qualifications and technical skill-set.  Shortlisted candidates will be required to arrange recommendation letters from two experts who are familiar with his/her work. The positions come with a competitive salary determined based on the selected candidate’s qualifications and experience.

Closing date: March 15, 2021. Applications will be considered as they arrive and the search will be considered closed immediately upon finding a suitable candidate. 


Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
www.sutd.edu.sg
email address
 
Singapore University of Technology and Design
8 Somapah Road, #07-101, Building 1, Level 7
Singapore 497372