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areas: Time-series analytics or forecasting Natural language processing (especially question answering or language grounding) Multimodal learning (e.g., combining text with temporal or numerical data
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Forecasting (CGF) at NTNU. CGF is a centre for research-driven innovation and is funded by the Research Council of Norway and industry partners. The immediate leader is Head of Department. Duties
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Forecasting (CGF) at NTNU. CGF is a centre for research-driven innovation and is funded by the Research Council of Norway and industry partners. The immediate leader is Head of Department. Duties
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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complex, multi-model ecological forecasting workflow. The fellow will gain valuable experience in advanced model development, calibration, and synthesis of the forest succession, fire severity, and climate
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successful appointee will be centrally involved in the delivery of the ARIA-funded Forecasting Tipping Points programme , and will work collaboratively with Professor Doug Benn (University of St Andrews) and
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convolutional neural networks (CNNs), generative AI methods such as diffusion models, and interpretability techniques commonly applied in hydrology including SHAP or LIME for explaining outputs of forecasting
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in real-world public health applications, including pandemic preparedness, outbreak forecasting, and integrating diverse data sources to inform decision-making. PREFERRED QUALIFICATIONS: PhD in
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at ICLR 2024 10 papers with MLG authors will appear at ICLR 2024 in Vienna, Austria. May 7, 2024 Google Summer of Code and Turing.jl We’re happy to announce that Turing.jl, a probabilistic programming