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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat
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before application deadline. Strong programming skills and experience with AI, computer vision, image analysis and deep learning are advantages. Knowledge of hematology, cytology and pathology is a plus
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processing and machine learning, as well as, online control of assistive systems. The PhD position is located in Aalborg, and the candidate will be a member of Neurorehabilitation Systems group at the Health
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to calculate your points for admission. Emphasis is also placed on your: background in algebraic or symplectic geometry or mathematical physics programming skills and experience with computer algebra packages
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: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including Information
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or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
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causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural Language Processing and LLMs; R; Python
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural