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specimens to estimate historical age structures over the last 150 years. Forecasting Shifts in the Pollination Service Window. The researcher will use Bayesian inference (e.g., Integrated Nested Laplace
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of advanced modelling and machine learning methods, and may involve the following areas: Dimensionality reduction. Data-driven methods for estimating dynamical models Data-driven methods for estimating
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– Humanity and Society (WASP-HS - https://wasp-hs.org/ ). Qualifications Requirements A doctoral degree or an equivalent foreign degree. The subject of the degree should be human aspects of ICT, human computer
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Experience of research in a laboratory is a plus Experience in systems programming and computer security is advantageous Scientific skills. Educational ability. Awareness of diversity and equal treatment
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experimental validation of cyclist speed over given routes. The background: When designing infrastructure, costs are crucial and can be estimated quite well. In contrast, user benefits in terms of reduced travel
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diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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criteria: Documented knowledge, preferably from his / her university education, is required in: mathematics, especially differential equations; numerical methods and computer programming; physical
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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streams, contributing to elevated environmental mercury levels and increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one