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, machine learning, etc. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and microwave engineers, computer scientists, software
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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has aimed to develop a two-part research programme. The first part focuses on developing and applying methods for 3D digital modelling, ranging from the collection of digital data from archaeological
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geometries. However, AM-generated surfaces exhibit significant and highly irregular roughness, a key factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify
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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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the development, training, and validation of computer vision models is comfortable working in multidisciplinary research environments, where methods are applied to biological or real-world problems Qualifications
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supervision The following experience will strengthen your application: Advanced coding skills (Python, R, etc.) Expertise in GIS and data visualisation. Experience applying Machine Learning, particularly
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep