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Field
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
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. Applications by email will not be considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting
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, STATA, SAS or other statistical packages; demonstrated expertise in the analysis of large and complex datasets; excellent written and oral communication skills in both English and Chinese (Cantonese and
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skills: Experience with machine learning and statistics Knowledge on mutational mechanisms in cancer Publications as co-author or first author in a related area Fellowships, grants and prizes Place of
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modified RNA and DNA molecules Supervise Sophie Davis and/or CCNY students in bench work and laboratory techniques Collect, record, and analyze experimental data using basic statistical methods Collaborate
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methods experience in the statistical analysis of research results or willingness to acquire such experience willingness to conduct a research stay for several month at another institute very good knowledge
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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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skills (e.g., programming, statistics) or a willingness to develop them will be considered particularly important for this project. Admission Regulations for Doctoral Studies at Stockholm University. About