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Field
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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is to explore and use available data sources to estimate prevalence of key infections (tuberculosis, HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV)) among migrants to high-income countries
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would co-develop the research objectives and select the methods to be implemented with supervisory support. Some ideas to discuss include integrating repeat GEDI LiDAR surveys with time-series
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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mining. Project description The knowledge of the mechanical behaviour of tailings is the background of all safety and risk analysis related to tailing dams independent of their construction methods. It is
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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. The candidate will contribute to the development of empirically validated methods for identifying and mitigating such effects. The research will involve experimental studies, neurophysiological methods (e.g., eye
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-based method to approximate the CFD-revealed effects of liquid metal convection on molten pool temperature predictions. • Designing and conducting instrumented WA-DED experiments to validate the developed
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Short overview of PhD opportunity The PhD studentship aims at studying and developing more comprehensive user interfaces for computer-aided decision-making processes, which can benefit from 3D/360