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- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
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Field
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comfort throughout the year in a Nordic climate? Is it possible to predict dynamic outdoor thermal comfort with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead
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treatments for mental illness. To this end, we bridge computational models that target various levels of analysis, including the algorithms (e.g., reinforcement learning models) and their neural
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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machine learning Data analysis and advanced statistics Economic and social transformations related to digitization Experince when it comes to programming (preferably Phyton) and in the use of modern tools
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market using data available on online recruiting platforms, deploying state-of-the-art approaches in Natural Language Processing, Semantic Web, and Agent-based Modeling. For this purpose, an extensive
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ADC performance against acute myeloid leukaemia (AML). Laboratory experiments and machine learning models will be implemented to achieve the following aims: Develop a random forest regression model
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, ranging from antibacterial to anti-cancer drugs. To this end, we develop new ways to combine state-of-the-art technologies in metabolomics with mathematical modeling. The candidate will have the opportunity
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trustworthiness of mathematical models and machine learning tools (e.g., neural networks) in a meaningful way, we need innovative, scalable methodologies that efficiently and accurately capture, represent, and
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research