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The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate
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Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
-world policy applications to equip students with the knowledge and tools needed to engage with AI at both strategic and operational levels. Students will learn how modern machine learning models work
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process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support process and
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23 Feb 2026 Job Information Organisation/Company Instituto Politécnico de Setúbal Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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Qualifications Bachelor’s Degree in a science-related field or Engineering to include: Aerospace, Biosystems, Chemical, Civil and Environmental, Computer Science and Software, Electrical and Computer, Industrial
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teaching and demonstration areas, will maintain these areas and assist in supporting program participants and volunteers engaged in learning opportunities on site. Responsibilities Job Duty Function Prepare
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, United States of America [map ] Subject Areas: Electrical and Computer Engineering / artificial intelligence , Artificial Intelligence and Machine Learning (AI/ML) Starting Date: 2026/01/01 Salary Range: $62,232-$80,000
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Learning Assistant/Remedial Tutor in Mechanical and Aerospace Engineering: Summer 2026 (Anticipated)
Computing ME 120: Component Design ME 137: Computer Aided Engineering Other courses as needed See catalog for course descriptions. A Learning Assistant works with groups of students on challenging course
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time