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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE GIURIDICHE | Italy | 3 days ago
. Where to apply Website http://www.unibo.it Requirements Additional Information Eligibility criteria to apply for research grants fill out the form available at the following address: https
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 1 day ago
or almost completed) in Physics, Applied Mathematics, Complex System or a related field. Strong background in mathematical modeling, machine learning, or biophysical simulations. Demonstrated interest in
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related field, with experience in one or more of the following areas: quantitative modeling and statistical-mechanical theory physical theories of allostery and mathematical modeling biophysics of receptor
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of mathematics, to develop innovative application-oriented mathematics with a focus on data-driven modelling, simulation, and optimization, and to open new mathematical thinking spaces. MATH+ is supported by
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At the Faculty of Engineering and Science, Department of Mathematical Sciences, one or more PhD stipends/Integrated PhD stipends in inference and modeling of Quantum transduction processes
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and limited resources (fleet size, mobile and fixed charging infrastructure). This project aims to address these challenges by developing novel mathematical models and algorithms to support real-time
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kinetic models and their hydrodynamic limits. Dispersive phenomena in kinetic theory. Quantum gases. Applicants must hold a PhD degree in mathematics, physics or a related field. We seek candidates with
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the requisite experience. A2 Knowledge of mathematical and statistical methodologies including several of: Statistical modelling and inference, Bayesian statistics and probabilistic modelling, Inverse problems
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Project summary: This PhD develops and evaluates a GPT-based AI co-facilitator for Group Model Building (GMB) workshops, supporting stakeholders in constructing Causal Loop Diagrams of complex socio
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. IRT relies on statistical models in which an unobservable quantity—the latent variable—represents the ability or trait score. However, this latent variable is not uniquely defined, as an infinite number