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research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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drug synergy research with an industry partner. Qualifications An MS in computer science, data science, computational biology, or bioinformatics with a heavy focus on machine learning and AI model
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Information Additional comments Candidate profile Applicants should hold a Master's degree in optics, physics, computer vision, deep learning, or a closely related discipline, obtained with a strong academic
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selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Personal
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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Experience with AI / probabilistic AI / Machine Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Experience with predictive maintenance, fatigue, fault detection
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- When and where do we reach the limits of adaptation to riverine flood risk?”. You have experience in machine learning, programming and flood risk research. If so, we encourage you to apply! You will
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high-quality research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition