ExxonMobil Info Session at UF

Shape the future of AI, Optimization & Computational Sciences at ExxonMobil

PhD Positions (Internships | Postdocs | Full-Time) 

Join us at our information session to find out more! 

When: Sept 15 | 3pm – 5pm

Where: MH 5210

 We'll start with a 30-minute presentation and then stick around to answer questions and connect one-on-one.  Bring your resume and come introduce yourself! 

ExxonMobil is seeking PhD candidates for internship, postdoc, and full-time positions to join our AI & Data Science, Mathematical Optimization, and Computational Sciences organization. 

Leverage your expertise in AI, data science, applied mathematics, optimization, computational science, and/or engineering to help develop state-of-the-art models and solutions. You'll work creating and improving physics-based models, advanced algorithms, AI/ML models and innovative numerical methods using a combination of cloud-based technology stack and state-of-the-art high-performance computing systems, including Discovery 6 (ExxonMobil’s Top 20-ranked supercomputer) to solve complex, real-world challenges across a variety of domains including Upstream, Manufacturing, Supply Chain, Commercial and Trading. 

Can’t make the info session?  You can also find us at the following career fairs:

  • Sep 14: CISE & AI Fair (1pm – 6pm)
  • Sep 16: Career Showcase (9am - 3pm) 

Additional Details on Opportunities

Note: Employment sponsorship available for qualified PhD candidates. 

Job Postings

Full-Time Position for PhDs

Intern Positions for PhDs

Postdoctoral Researcher Position - Explainable AI for 3D Data Job Details

Postdoctoral Researcher Position - Multimodal Knowledge Extraction and Reasoning Job Details

Additional postdocs opportunities in Simulation & Digital Twin Modeling, Optimization with Embedded Machine Learning Surrogates, and Scientific Machine Learning will be posted soon. 

What your work will look like at ExxonMobil

  • Partner with stakeholders to understand their workflows and translate business questions into modeling problems.
  • Design, develop, validate, and maintain data‑driven and first‑principles models supporting business decision-making.
  • Apply appropriate modeling techniques with a focus on business interpretability, robustness, and decision impact.
  • Collaborate closely with data engineers, software developers, and other data scientists to integrate models into scalable, enterprise‑grade AI solutions.
  • Act as a bridge between AI/Data science and the business domain by clearly explaining assumptions, limitations, and actionable insights to non‑technical business partners.
  • Monitor and improve model adoption by working with users to embed models into decision‑making processes. 

Business Challenges We Solve

  • Subsurface & Wells (well construction cost reduction and negative incidents identification)
  • Commercial & Trading (acquisition/divestment decisions, macroeconomic and market modeling, asset valuation, and dynamic pricing)
  • Maintenance (reliability across global assets)
  • Global Projects (decision quality in concept selection, development planning, and systems completion)
  • Exploration (insights from large, multi-disciplinary datasets)
  • Production Optimization (margin improvements across upstream assets and manufacturing sites)
  • Value Chain Optimization (tactical and operational LNG supply and downstream supply chain decisions)
  • Molecule Optimization (profit optimization applied to the integrated value chain) 

Active R&D Areas in Data Science

  • Multimodal Models, Domain-Specific Models and Generative AI Models
  • Time Series Forecasting & Causal Inference
  • Advanced Reasoning
  • Knowledge Representation
  • Agentic AI systems for high-stakes decision making
  • Explainable AI
  • Application Areas: Supply Chain, Manufacturing, Commercial & Trading, Exploration, Global Projects, Subsurface & Wells, Maintenance 

Active R&D Areas in Optimization

  • Optimization with ML-Based Surrogates
  • Leveraging LLMs in Optimization Workflows
  • Cloud Computing for Optimization
  • Next-Generation Compute Platforms
  • Application Areas: Upstream Development Planning, Maritime Logistics Optimization, Supply Chain, Production Planning and Deployment Optimization, Manufacturing 

Active R&D Areas in Computational Sciences

  • Scientific Machine Learning
  • Multiscale Multiphysics Modeling
  • Inversion
  • Application Areas: Upstream Exploration and Development, Carbon Capture Solutions

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