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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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options to extend the position to related research projects. Job description The Research Fellow will contribute to: Identifying topics in AI research (publications) and inventions (patents); Estimating
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to start > Demonstrates strong “hacking” ability to quickly get into data to look for empirical relationships and decipher noise or signal > Familiarity with classical statistical methods and knows when and
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Operations Research, in particular on exact and approximate methods in Markov decision theory. Our new colleague is envisaged to work on applications in healthcare optimisation, but also expand the current
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass
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will focus on developing novel AI-driven methods for modelling, estimation and control of brain dynamics – time-dependent patterns of neural activity fundamental to brain function, behaviour and
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technology model that analyses integrated satellite and ground-based sensor data; estimating European launcher carbon footprint, energy security and energy cost savings; proposing meaningful carbon footprint
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in-depth experience in one or more specific technical domains covered by the position Experience with the design, development and application of relevant tools and methods Understanding of related
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, conventional methods for in-situ data collection—typically involving manual interpretation of high-resolution satellite imagery via 2D web-based interfaces—can be time-consuming and prone to interpretation