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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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Dr. Darius Bunandar, the Boston University team is led by Prof. Ajay Joshi, and the Harvard University team is led by Prof. Vijay Janapa Reddi. Role Our team has two postdoctoral researcher openings
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Australian National University | Canberra, Australian Capital Territory | Australia | about 19 hours ago
to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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collection algorithm participate in data collection and dataset creation assist in quantitative data analysis collaborate on writing academic articles and research reports Where to apply Website https
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 6 days ago
Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human