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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key
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processes under different biological conditions. Apply statistical learning, deep learning and probabilistic modelling approaches to large-scale cancer datasets. Evaluate and benchmark computational methods
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on a project in the area of power system risk modeling and assessment. Key Responsibilities: Develop a probabilistic security assessment framework for heterogeneous operational uncertainties and
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-scale inverse problems by combining interpretable high-level probabilistic models, multi-physics data integration, and modern machine learning. The resulting methods will be validated on groundwater
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) Familiarity with mathematical programming solvers (e.g., Gurobi, CPLEX) or probabilistic/Bayesian computing frameworks (e.g., Stan, PyMC) Ability to formulate high-impact, novel and well-defined research
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skills. Experience in probabilistic analysis and uncertainty quantification within an engineering context, a track record of high-quality peer-reviewed research, and the ability to work independently and
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supervision in dealing with data uncertainties. He/she will be responsible for Modelling propagation of earthquake motion from source to site Perform probabilistic seismic hazard analysis (PSHA) Perform
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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning
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, behavioural evaluation, probabilistic modelling and ideas from cognitive science, neuroscience and theories of learning. The broader aim is to develop methods that support high-confidence claims about the goals
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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