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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict
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activities: · Understanding/simulating the diffusion paths and cavitation in thermoplastic liners. · Multi-physics simulation of the diffusion process in thermoplastic orthotropic composites
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of bioinformaticians, computer scientists, biotechnologists, biologists, and biochemists. The successful candidate will also enjoy an environment aimed to facilitate progress in the research career: networking, student
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for the following research themes: Heterogeneous Catalysis Metal Capture from Water Electrochemical Water Splitting Process Design and Scale-up
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, the generated data can be used to optimize mineral extraction processes from existing mines within a geometallurgical framework. The position will mostly focus on the development of measurement protocols and data
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of lithium-ion battery recycling. The focus of this position is on material recovery from cathode materials through a groundbreaking filtration and extraction processes. Key Responsibilities: Participate in
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groundbreaking filtration and extraction processes. Key Responsibilities: Participate in and lead the development of lithium-ion battery recycling technologies. Develop advanced separation technologies including
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of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc students
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technologies. Key Responsibilities: Develop and optimize hard carbon synthesis processes using bio-based and non-bio-based precursors. Explore innovative methods to enhance material properties for energy storage
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Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related