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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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conversion of CO₂ into renewable fuels. Central to this effort is the investigation of advanced catalytic systems that bring together multiple functionalities, including components responsive to plasma
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diffusion models usually needs to access a pre-trained model multiple times sequentially to generate high-quality images or videos, which is time-consuming. The training process of diffusion models is also
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array antenna systems for imaging MIMO radar in autonomous driving applications. This work will advance the design and characterization of intelligent devices and environments for wireless communications
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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MSc/PhD Position at the Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Canada
research project focused on exploring the immunometabolic pathways of macrophages and microglia in multiple sclerosis (MS). The Kaushik Lab is committed to fostering an inclusive and equitable research
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dysfunctions result in rare human diseases known as ciliopathies that affects multiple organs leading to clinical manifestations such as blindness, deafness, obesity, mental retardation, renal and breathing
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lizard tail regeneration sheds light on their neglected importance, with potential applications in scar-free wound healing research. Overall, this research has broad-reaching implications in multiple
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project TARGET-AI will bring together expertise from multiple research groups to advance the state-of-the-art in combining the most advanced techniques from deep learning/AI with rigorous statistical
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks