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Field
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tackling the above challenges with novel system designs and tailored AI/ML based methods. Candidate’s profile A First Class Bachelors degree and/or Masters degree in a relevant subject (computer
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-related transport phenomena all require precise knowledge of fluid flow dynamics. Advanced experimental methods such as Particle Image Velocimetry (PIV) and 3D Lagrangian Particle Tracking (LPT) provide
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Materialist theories Developing appropriate (design) research methods Project management About the project:Thinking with Things is funded by the Austrian Science Fund (FWF) and will start on January 1, 2026. It
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to neurodevelopmental conditions caused by prenatal alcohol exposure, with a UK prevalence estimated at 3.2%, among the highest globally. Individuals with FASD commonly experience challenges with learning, memory
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by developing AI methods that improve recognition of rare species while providing reliable measures of uncertainty. Using state-of-the-art computer vision approaches — vision transformers, self
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to quickly quantify the damage to forest plantations after a cyclone or a tropical storm. There is unrealised potential in using multi-modal computer vision methods that synthesis multi-source Earth
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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-driven modelling and numerical mathematics leading to computationally fast methods State-of-X (where X is charge, health and/or function) estimation at the pack level. This requires developing
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24 Nov 2025 Job Information Organisation/Company Computer Vision Center Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R