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description: Work Area: Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems Project overview: Processing of physiological and inertial signals
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series
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developed: Collaborate in studies of a combinatorial optimization problem of current interest. Propose new algorithmic solutions for its resolution. Cooperate in the extensive experimental analysis
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developed: Collaborate in studies of a combinatorial optimization problem of current interest. Propose new algorithmic solutions for its resolution. Cooperate in the extensive experimental analysis
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research strand 3 «Addressing key methodological challenges». The positions are tied to CREATE’s strand 3. Strand 3 aims to develop novel methods and statistical software that are tailor-made to the research
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under
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of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well. The candidate’s work will entail the development and
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. The candidate will develop DRL algorithms for online and off-line tasks, for robotic applications and possibly for LLM reasoning applications in the future. The work will involve designing algorithms, running
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. This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design, and
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in Summer 2026, for a term of 2 years with the possibility of an extension. The postdoc will join the ERC-Starting Grant project team on “Participatory Algorithmic Justice: A multi-sited ethnography to