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Field
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comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and mapping them onto phylogenetic trees Collaborating with a multidisciplinary team of biomechanists
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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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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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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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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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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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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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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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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