79 parallel-computing-numerical-methods-"Simons-Foundation" positions at Aalborg University in Denmark
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The Department of Computer Science at The Technical Faculty of IT and Design invites applications for PhD stipends on one of the topics of Digital Twins and Hierarchical Multi-Agent Safe
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, Denmark [map ] Subject Areas: Nonparametric estimation, Machine learning methods in econometrics and time series analysis, Statistics for high-dimensional data, Stochastic volatility models Appl Deadline
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with
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environment. This includes developing low embodied carbon materials and solutions, and extending the lifetime of structural components. Specific fields of interest include simulation methods, computational
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nexus supported by data-driven methods. This is a full-time position, expected to start on 1st of February 2026 or as soon as possible thereafter. This position is a six-year position as an assistant
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method development and DNA library preparation for Oxford Nanopore sequencing. Large experience in bioinformatics, machine learning and high-performance computing. Furthermore, excellent written and oral
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the interplay between qualitative and quantitative methods and data. There is a growing focus on novel computational methods such as NLP, machine learning, and AI within the group. Teaching activities in
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performance, and preventing failures like fires or explosions. Current prediction methods mainly rely on extensive lab testing and modeling, using insights from destructive post-mortem analyses to improve
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Graph Machine Learning and Graph Data Management At Section for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk
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research in Time Series Analysis and Econometrics with focus on one or more of the following key research areas: Nonparametric estimation. Machine learning methods in econometrics and time series analysis