Postdoctoral Researcher Optimization with Embedded Machine Learning Surrogates
Employment type
Full-time
Work setting
On-site
Location
Spring, TX
Schedule
Day shift
Posted
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Job overview
The Postdoctoral Researcher in Optimization with Embedded Machine Learning Surrogates is an onsite role based in Spring, TX. Compensation is not specified for this position, which supports ExxonMobil's research into advanced optimization and machine learning techniques. This role exists to integrate mathematical optimization and machine learning through surrogate modeling. The researcher contributes to the company's goals by developing scalable solution algorithms for high-value business applications.
What you'll do
- Develop optimization frameworks with embedded ML surrogates, design formulations integrating neural networks, investigate trade-offs, and develop specialized solution algorithms.
What we're looking for
- Skills & competencies
- full-timeday shiftspring txexxonmobilpostdoctoraloptimizationmachine learningsurrogate modelingoperations researchpythonresearchph.d.
- Work arrangement
- Weekend coverage required
Benefits & perks
- Comprehensive health, security, finance, and life benefits
- relocation assistance may be available.
Why this role
Focus on the intersection of Operations Research and AI for industrial decision-making.
About the employer
ExxonMobil is hiring for this role. Industry: Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology). Sector: 54.
Additional details
- Industry sector
- 54
- Industry
- Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Occupation code
- 15-2031.00
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Listing ID: 2ebe9b5e-54ae-4d95-a30d-2d8ddf77eef9