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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 11 hours ago
University of Science and Technology (KAUST) Open Date Feb 12, 2025 Description We are seeking motivated researchers with expertise in large-area 2D materials growth for sensor and transistor applications. The
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evaluating their performance relative to classical machine learning and statistical methods. The research would combine algorithm development with implementation and evaluation on current quantum computers
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environment. REQUIRED : Ph.D. in computer science, mechanical engineering, applied math, or related field with significant research experience in machine-learning/AI algorithm development, specifically in
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computational methods, working with large and heterogeneous datasets, evaluating algorithm performance and uncertainty, and translating research methods into reproducible scientific software and analyses. The
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hardware and FPGA background, who is interested in contributing substantially to both research and teaching. The ideal candidate should enjoy developing complete embedded systems, from sensor and
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, printed, bio-, and soft electronics. The present position is part of the Swedish Research Council (VR)-funded project “Biowaste-Based Stretchable Sensor Modules for Sustainable Plant Wearables
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research in luminescence and sensor development, provide research training to undergraduate students, support teaching laboratories and research facilities at the Interdisciplinary Materials Research
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department by predicting defects and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core
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Research experience that includes medical image processing, Artificial Intelligence (AI) algorithm development, and scientific writing. Gain clinical experience including training in radiation oncology
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fruit. This variability makes it difficult to predict ripening behaviour and consistently deliver fruit at the required quality while minimising energy use and waste. Recent advances in sensor