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Sr. Artificial Intelligence Lab Scientist - Material Discovery (1844)
Aramco Services Company
📍
Houston, United States
Location
Houston
Posted
June 08, 2026
Commute
Local Area
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Job Description
OVERVIEW:
Aramco Americas is establishing a state‑of‑the‑art research center in Houston dedicated to advancing CO₂ capture, low‑carbon liquid fuels and chemicals, renewable energy, and energy storage solutions, as well as artificial intelligence applications in the energy sector. The center’s mission is to transform early‑stage, low‑TRL research into mid‑level technologies (TRL 5–7), bridging the gap between fundamental discovery and practical deployment.
SCOPE:
Aramco Americas is seeking an experienced scientist specializing in the application of Artificial Intelligence (AI) and Machine Learning (ML) to accelerate next-generation materials discovery for carbon capture and utilization, catalysis for synthetic fuels and chemicals development, and related sustainable energy technologies. The role will apply AI/ML-driven modeling, simulation, and data analytics to understand and predict material structure-property-performance relationships and link th...
Aramco Americas is establishing a state‑of‑the‑art research center in Houston dedicated to advancing CO₂ capture, low‑carbon liquid fuels and chemicals, renewable energy, and energy storage solutions, as well as artificial intelligence applications in the energy sector. The center’s mission is to transform early‑stage, low‑TRL research into mid‑level technologies (TRL 5–7), bridging the gap between fundamental discovery and practical deployment.
SCOPE:
Aramco Americas is seeking an experienced scientist specializing in the application of Artificial Intelligence (AI) and Machine Learning (ML) to accelerate next-generation materials discovery for carbon capture and utilization, catalysis for synthetic fuels and chemicals development, and related sustainable energy technologies. The role will apply AI/ML-driven modeling, simulation, and data analytics to understand and predict material structure-property-performance relationships and link th...