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starting the PhD). The candidate must be qualified for admission to the ph.d. program Strong background in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python
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. Documented experience with Bayesian spatiotemporal modelling, including experience with the INLA framework for Bayesian inference Documented experience with programming in either Python or R. Foreign completed
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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, freely-behaving recording procedures, signal processing and data analyses Experience with rodent development, colonies maintenance Fluent oral and written English communication skills Python, Matlab, R
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analysis). Skills in programming and scripting languages (Python/R/Matlab). A strong command of oral and written English. It is an advantage if you have Experience with cloud-based compute infrastructure
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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, neuroscience, medicine, or similar Experience as clinical psychologist and with structured clinical assessments Expertise in statistical analysis using R or similar Experience with big data analysis with high
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or R. Fluent oral and written communication skills in English is required. At least two of the following qualifications are also desired. Experience in petrography and analysis of rocks (SEM, EPMA, Raman
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techniques for screening plasmid libraries, such as phage display and yeast display is an advantage. Coding abilities in R/Python are an advantage. The candidate will work in a very ambitious interdisciplinary
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, psychology, or equivalent statistical genetics expertise and hands-on experience with high performance computing and big data analysis skills in programming and scripting languages (R/Python/Matlab) excellent