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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
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carbon stock estimates within the project “A better check on soil carbon - a novel sampling and measurement approach for improved precision in soil carbon monitoring”. Important parts of the work
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increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one of the top three sources of anthropogenic mercury emissions worldwide
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qualifications Doctoral degree or equivalent international degree in Cognitive Science, Psychology, Affective Neuroscience, Human–Computer Interaction, or a closely related field. This requirement must be
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employed in the Cybersecurity division with close to 50 members at the department of Computer and Information Science (IDA) . You will work together with Simin Nadjm-Tehrani, professor in dependable systems
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-form empirical research with large datasets. This includes strong programming skills in Python and experience with at least one additional language used for structural estimation or numerical computing
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sensing data which estimate forest biomass, e.g. from airborne and spaceborne laser scanners, since no in-situ based biomass data with global coverage exist. Who we are looking for The following