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Field
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exposure methods to enhance comprehension of material corrosion in hypersaline environments. Reliable test methodologies and statistical analysis techniques will be employed to assure conclusive
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trajectories. Leveraging deep learning, generative models and cross-modal autoencoders and working with both structured and unstructured data, the goal of this project is to develop a statistical framework and a
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Department of Mathematics and Mathematical Statistics Temporary position 100% Umeå Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700
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analysis in biomedical data, in affiliation to the Artificial Intelligence Research Centre . The successful candidate will develop statistical and machine learning techniques to analyse biomedical data. High
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usefulness of the forecast, and perception of forecast performance by the public. Statistical post-processing techniques can help to reduce forecast errors by training machine learning models on data sets
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candidate under the supervision of Dr Luca Ambrogioni. We carry out research at the frontier of generative modelling using concepts from statistical physics and neuroscience. For example, we have shown
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, outcomes, and real-world impact. The student will be supported by a supervisory team including Professors in hepatology and epidemiology, and experts in computational statistics and model fitting using
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occurrence, aetiology, outcomes, and real-world impact. The student will be supported by a supervisory team including Professors in hepatology and epidemiology, and experts in computational statistics and
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generalisability compared to traditional adaptive control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Mathematics and Mathematical Statistics is opening a PhD position in Computational Sciences