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the Mechanical Engineering Program. This position covers the applications of artificial intelligence and data-driven methods to understand, design, and optimize complex energy systems and devices. Example topics
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community. Working under the AI/ML Support Team Lead, this role focuses on developing and optimizing Generative AI models, maintaining computational benchmarks, and providing expert consultation
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Full-time Hours Per Week 40 Offer Starting Date 9 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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to provide technical oversight in these partnerships, to guide designers, engineers and operators from a grower’s standpoint, and to manage the design, delivery, analysis and reporting of a trial program. The
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 4 hours ago
include, but are not limited to: Seawater reverse osmosis process optimization Next-generation membrane and separation technology Energy-efficient desalination Brine management, zero-liquid discharge and
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. This includes large-scale computational mechanics of energy structures, data-driven mechanics, reduced-order modeling, structural optimization, life-cycle analysis, multiphysics modeling of energy materials, and
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Position Summary Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network
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collaborative research program. Maintain rigorous experimental records and reproducible protocols. Develop mechanistic understanding beyond empirical optimization. Publish in high-impact journals in materials
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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optical, electronic, and photodetector properties. Responsibilities Synthesize III–V CQDs using air-free colloidal methods. Design and optimize precursor chemistry for InAs-, InSb-, Ag₂Te-, and PbSe/PbS