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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
collaboration with other researchers. The key topics of PREDICT (and the candidate’s potential line of research) are: Machine learning-based probabilistic hydrological modelling, including calibration, validation
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, and in collaboration with Previsico Ltd. and the US Geological Survey, the researcher will combine fieldwork, remote sensing, and modelling (using CAESAR-Lisflood) to quantify how burned landscapes
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Your job Are you fascinated by using mathematics to solve fundamental questions in ecology? Do you thrive on translating abstract models into biological insight? If so, this PhD opportunity could be
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learning models without moving sensitive or large-scale datasets across systems. The project will focus on designing a modular framework that addresses security, privacy, governance, and performance, while
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of Higgs boson pairs. These decays, which are 1000 times more rare than single Higgs production according to the Standard Model have not yet been observed. Observation of two-Higgs production is one the most
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the most efficient analytical approach (e.g. weight, profilometry, SEM) to calibrating the quality model? How can AI based methods be used to fit empirical data to existing nanofiber quality models
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design of multi-armed bandits and reinforcement learning models with applications to recommendation systems and clinical trials (Gui Liberali), privacy (Gilian Ponte), causal inference (Jason Roos
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innovation management involves all actions needed to generate creative ideas and to turn these into attractive new products, services, and business models. The Innovation Management group at RSM is a team
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Energy Districts through citizen-centered socio-technical models for upscaling of the heat transition – seeks to tackle this challenge by involving key stakeholders (citizen groups, municipalities, housing
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contribute to the design and development of Machine Vision approaches for the quantitative analysis and phenotyping of agricultural systems: Training/Development of computational models for the quantitative