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Modeling naturally fractured reservoirs is re-gaining interest in the Oil & Gas industry and academia for application in carbonate fractured reservoirs and unconventional reservoirs where natural
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learning, computer vision, and natural language processing. You will have the opportunity to boost your career development and training, read more here . Post-docs receive highly competitive salaries and
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The lab of professor Jesper Tegnér at KAUST has openings for three postdoctoral fellowships in Data-driven Machine Learning for unbiased Discovery of Generative Models with special reference
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environment with researchers from over 100 nationalities Post-docs receive highly competitive salaries and other benefits, inclusive of accommodation, healthcare, medical and dental insurance, relocation
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feasibility studies of CCS using mechanistic modeling and simulation including uncertainty analysis and risk assessment. Applications are sought for a 1-to-2-year postdoctoral fellow position. The position
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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environment dediacated to the wellbeing and career success of Fellows and their families. Eligibility Requirements Ph.D. in a discipline related to KAUST’s research priorities Up to 4 years of post-PhD
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years of post-PhD experience (Ph.D. awarded after January 2022) Demonstrated strong communication skills and fluency in English Submission of an innovative research proposal aligned with KAUST priorities