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systems. Specifically, the research will propose an integrated framework that will couple two core components: 1) advanced algorithms to optimise participation of HPPs, or more generally of VPPs integrating
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following fields (preferably several): recommender systems, user modeling, algorithmic fairness and ecological aspects (e.g., of recommendation algorithms/systems), simulation studies (e.g., simulation
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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the human musculoskeletal system, or experience providing engineering, hardware, statistical, or algorithmic support for such research (e.g., in biomechanics, biomedical signal processing, analysis of data
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intended for a senior researcher with a highly specialized interdisciplinary profile at the interface of graph theory, combinatorics, exact graph algorithms, molecular graph analysis, cheminformatics, and
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surfaces. (iii) Optimize and enhance the computational algorithm by introducing a patterned spintronic THz emitter array to resolve the two-dimensional object image from the data set in real-time
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logistics. The research activity will develop models and algorithms that exploit communication infrastructure and data availability, enabling the optimization of the required resources. In the case
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results in the areas of geometric data science and machine learning Designing, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing
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algorithms will subsequently be developed, trained and tested to identify markers of reduced brain resilience during ageing. The project adopts an interdisciplinary approach at the interface of neuroscience
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. The Role Faculty of Environment, Science and Economy The successful applicant will contribute to the project NATALIE by developing AI algorithms that integrate data from various sources to better understand