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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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-powered diagnostic algorithms, and integration with digital health platforms for real-time monitoring and clinical decision support. WITEC brings together interdisciplinary researchers from MIT and
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manufacturer. Based on our publication (ACS Appl Nano Matter 2022, 10.1021/acsanm.2c03406) and our ongoing collaborative work, we have developed a new chemical assay coupled with a machine learning algorithm to
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. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized
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to ensure that the developed notations and algorithms address the companies’ needs. More about the related project can be found here: https://innovationsfonden.dk/da/news-article/ai-skal-forudsige-og-forklare
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research in machine learning (ML) for applications in High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time
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using both physical and machine learning-based algorithms. Strong interpersonal and communication skills and the ability to work both independently and collaboratively with researchers and students from
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to algorithms, and cross-platform co-design across superconducting, neutral atom, and diamond-based systems, guided by quantitative resource estimates targeting DOE-priority scientific applications. Position
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are looking for a postdoctoral researcher in the field of image generation algorithms (specializing in Deep Learning) for a 12-month position. The work will take place within the IMAGE research team