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Field
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: Developing innovative methods from the field of machine learning for biomedical data, e.g., explainability, interpretability, and causal inference Contributing to the design of novel algorithms and models
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% STFC:25% UoW split), gaining experience in algorithm development, experimental validation, software engineering, and scientific communication. Training opportunities include international workshops
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Contribute to the development of new algorithms and methods for the efficient analysis of large-scale omics datasets Participate in workflow automation and management using systems such as Snakemake
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. This evolution calls for new methodologies capable of effectively representing and compressing data in infinite-dimensional settings. In this project, we aim to address this challenge by developing a theoretical
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. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance, reliability, and availability of complex industrial systems while making maintenance strategies
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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locations in Frankfurt am Main and Berlin, DIPF develops and documents knowledge about education and thus supports science, politics and practice. The Information Center Education (IZB) department is looking
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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or damage. Along these lines, this project develops SHM methods for deep tunnels, with the HADES Underground Research Laboratory (URL) serving as the primary case study. The monitoring strategy combines in
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are transparent, interpretable and aligned with human needs and values. You will focus on developing, testing and reviewing a methodology to make AI systems transparent and explainable. The goal is to empower