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Field
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conducting human studies with human participants including participant recruitment, data collection, and management of data Advanced skills in statistical analysis using software such as R, STATA, or SPSS
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motivated candidate with a background in neuropsychology, medicine, neuroscience, molecular biology, biostatistics, pharmacology, pharmacoepidemiology, public health, statistics or a related field. The
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will have a background in computational sciences or life sciences with a strong interest in applying these skills to environmental health research. Experience with programming, statistics, or machine
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evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
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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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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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workshops.The PhD students will focus on using state-of-the-art computational and statistical techniques to shed light on the fundamental mechanisms of decision-making.We are particularly interested in candidates
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, or related Experience and skills · Multi- and hyperspectral images processing · Knowledge of quantitative remote sensing · Knowledge of physical and statistical modelling concepts