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Field
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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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– with prior experience working with administrative data. Advanced skills in database management (i.e., SPSS,Excel) as well as advanced analytic approaches (i.e.,multivariate statistics) are required. SQL
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– with prior experience working with administrative data. Advanced skills in database management (i.e., SPSS,Excel) as well as advanced analytic approaches (i.e., multivariate statistics) are required. SQL
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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genetics, and may include expertise in one or more of the following: computational biology, statistical genetics, population genetics, biomedical informatics, complex genetics, clinical genetics
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change theory and practice, implementation science, and associated measurement and analytic techniques. The candidate is expected to help bridge these domains using validated statistical tools. Applicants
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multivariable statistical methods. Support for skills development is provided within the Horse Microbiome Research Group and the university’s Doctoral College . Delivery of this project in collaboration with
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the context of computing Familiarity with research tools and methods, including statistics platforms like R and/or thematic analysis Knowledge of user-centred design and research methods involving human
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appropriate statistical testing to test the efficacy of the models. The project forms part of a wider effort for developing an effective VR HRI toolkit for improving interactive fluidity between robots and