Analysis Fellow (Computational Surrogate Optimization in Python; Industrial Engineering) job with NATIONAL UNIVERSITY OF SINGAPORE
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Job Description
The profitable candidates will work with Prof. Shoemaker and her group to develop, implement and/or consider serial and parallel optimization algorithms for costly black-box fashions.
The optimization drawback may be anticipated to have a number of native minima/maxima. Surrogate strategies are thought of additionally since computational effectivity for computationally costly targets (e.g. simulations) is enormously enhanced with surrogate algorithms and has been coupled with machine studying to resolve complicated issues. A part of such algorithms are restart methods.
The candidate may have the chance to develop analysis expertise, take part in worldwide conferences, and work on the Singapore Supercomputer (NSCC).
Job Necessities
- PhD in Operations Analysis, Industrial/Methods Engineering, Utilized Arithmetic, Laptop Science or associated fields.
- In depth analysis expertise in computational optimization and good to wonderful functionality in python programming.
- Prior data of Computational Surrogate Optimization is a bonus. Data of other restart methods is a bonus.
Covid-19 Message
At NUS, the well being and security of our employees and college students are one among our utmost priorities, and COVID-vaccination helps our dedication to make sure the protection of our group and to make NUS as protected and welcoming as potential. Lots of our roles require a big quantity of bodily interactions with college students/employees/public members. Even for job roles that could be carried out remotely, there can be situations the place on-campus presence is required.
Making an allowance for the well being and well-being of our employees and college students and to higher shield everybody within the campus, candidates are strongly inspired to have themselves absolutely COVID-19 vaccinated to safe profitable employment with NUS.
Extra Info
Location: Kent Ridge Campus
Group: Faculty of Design and Engineering
Division : Industrial Methods Engineering and Administration
Worker Referral Eligible: No
Job requisition ID : 17796
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