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Field
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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world
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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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organizing collective behaviour Analysing interspecific variation in swarming behaviour using comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and
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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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dimensionality reduction as well as analysis of blood proteomic data. We are looking for a student with experience in bioinformatics and relevant statistical methods using R or Python languages. Some knowledge of
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal
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through the HR system. 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
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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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, 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