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researcher with expertise in the area of spiking neural networks and an interest in (applications of) probabilistic computing. The postdoc candidate will participate in the NWO NWA project "Acting under
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming
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. The position is associated with the project “Probabilistic Reasoning about Common Ground” under the auspices of the Collaborative Research Center “Common Ground” (CRC1718), which is funded by the German Research
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques
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-based, probabilistic, and in-memory computing, are based on a wide variety of physical processes, materials, architectures, and algorithms. For effective implementation, these aspects need to be mapped
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and analysis of probabilistic and social choice models, help with the design and conduct of experiments, perform literature reviews, and contribute to the drafting of technical reports and publications
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
). Probabilistic and reliability-based analysis applied to underground structures. Advanced subsurface characterization techniques integrating geotechnical and geophysical data. Geohazard mapping and modeling
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, Probabilistic Inference, Algebraic Topology and Wavelet analysis theory. Familiar with Matlab/Python/C++ programming. Experience with Pytorch and multi-GPU model deployment. Experience in analyzing complex