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these methods to detect micro-seismic events in borehole and underwater DAS data based on their long-range coherence rather than their energy [2]. Although they achieved superior performance and are built
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
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Master's degree in Epidemiology, Public Health or a related field. Applicants should be enrolled in a Master program and the internship should be a mandatory part of the diploma; Experience in working
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, ranging from biological to clinical features. The integration of such heterogeneous information within a coherent computational model is currently challenging, due to the typical large dimension and
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these applications are generating structured, high-dimensional data with non-trivial and intricate geometric properties. These data often display complex relationships and dependencies that go beyond
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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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, its features, or the actual model parameters, to (ii) poisoning attacks that target the integrity of the ML model and cause a general degradation of the performance of the model
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Ability to consistently meet deadlines through organized, methodological, pragmatic, and effective work practices Fluency in English is required. French or German is considered an asset We offer
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to consistently meet deadlines through organized, methodological, pragmatic, and effective work practices Fluency in English is required. French or German is considered an asset We offer Multilingual and
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We are recruiting a highly motivated and experienced researcher to develop and structure a research and educational program dedicated to kidney cancer. The position is supported by a 3-5 year fixed