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- University Medical Center Utrecht (UMC Utrecht); Published yesterday
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PhD studentship in the Probability and Statistics Research Group at the University of Sussex (UK) The Project Fourier analysis and abstract harmonic analysis provide powerful tools in many areas
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University Medical Center Utrecht (UMC Utrecht); Published yesterday | Netherlands | about 2 hours ago
validating a machine learning prediction model for CP and related outcomes using neonatal MRI, EEG, GMA, HINE, and clinical data. Coordinating patient inclusion, data collection, and analysis across multiple
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, and explore optimisation strategies for deploying these models in modern data analysis pipelines. You will have the opportunity to join the LIGO Scientific Collaboration as well as the team developing
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The interplay of TCS with Harmonic analysis and additive combinatorics There will be opportunities for collaboration with faculty members and PhD students and to engage with the broader quantum computing and
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mental health omics data more harmonized, accessible, understandable, and useful to researchers, clinicians, industry, and people with lived experience. You will work closely with a multidisciplinary team
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research themes include: off-momentum collimation in merger and arc sections, influence of higher-order magnetic harmonics, alignment errors and mechanical tolerances, wakefield effects in beam combination
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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of systems. We develop methods to advance sustainable energy and chemical process systems from the molecular to the scale of the systems. Our work combines process analysis and system modeling to design
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 2 months ago
models as predictive tools to address questions regarding the response of deep-sea ecosystems to various pressures. A key question addresses the best combination of ML and network analysis to maximize
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work will be focused on metals, pesticides, microplastics, PFAS, and nutrients. Key Goals: collection of known pollution-biota interactions (reviewing, organization and harmonization into a database