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strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
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furnace simulator, you will study the interaction, distribution and impact of alkalis and sulfur across BF and gas-based DR reactors. Their behaviour in direct reduction remains largely unexplored, making
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advanced computer vision, dedicated lighting systems, optical communication, and robust control and guidance algorithms. You will work on: Design and implement computer vision algorithms for accurate landing
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on wind turbines and ships. This involves advanced computer vision, dedicated lighting systems, optical communication, and robust control and guidance algorithms. You will work on: Design and implement
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there are many opportunities to interact. The research of the Nikhef theory group include higher-order calculations and jet physics in perturbative Quantum Chromodynamics, parton distribution functions
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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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motivation to independently formulate research projects and carry them through to completion; Mathematical skills and command of standard software packages for implementing of optimization algorithms, and a
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learning algorithms for early damage detection, health indicator extraction, and remaining useful life prediction. The successful candidate will take a leadership role in experimental integration and data
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and elicitation of informed prior distributions; Critical assessment of default prior distributions; Organizing a many-statisticians challenge and workshop; Studying model-averaging, effect size
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work with Dr. Anna Dawid and her research team. The position is set in the exciting, friendly, and interdisciplinary environment of the aQa (Applied Quantum Algorithms) group, which is a team of faculty