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need, this may be prepared from published field operation data, laboratory measurement or other sources. Machine learning can be used to select the bet data set for each particular cases covering
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-making. However, traditional machine learning models face limitations in this domain due to several critical challenges. First, ICU data are high-dimensional and multimodal, with patient states evolving
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main research topic for this position is to investigate the thermal break-up of pure polymers and composites using a combination of experimental techniques and chemical modelling. For a position as a
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well as candidates with a background in machine learning methods. The PhD programme will straddle the boundaries between the field of wave modelling and the general field of machine learning, and we will set up a team
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biodiversity or occurrence data (e.g., GBIF). Understanding of species distribution modelling or trait-based ecology. Interest or experience in applying AI or machine learning methods to ecological questions
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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, and entrepreneurship. Doctoral Candidates will gain transferable skills and learn from industry role models, equipping them to make significant contributions to solving the AMR crisis. The succsesssful