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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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the link "Apply for this job". The following documentation must be uploaded electronically: Certificates with grades Master’s thesis References Academic work and R&D projects, as well as a list of these An
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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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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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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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obtain binding data and high resolution crystal structures (Espeland LO, Georgiou C, Klein R, Bhukya H, Haug BE, Underhaug J, Mainkar PS, Brenk R. An Experimental Toolbox for Structure-Based Hit Discovery
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Language Processing and LLMs; R; Python. Applicants must be fluent in English. Applicants who have completed their education outside of the EU/EEA-area and who do not have English as a native language, must document
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experience with statistical programming in R or python Written and spoken English proficiency. As a general rule, the following normally apply: The average grade for courses included in the bachelor's degree
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Language Processing and LLMs; R; Python. Applicants must be fluent in English. Applicants who have completed their education outside of the EU/EEA-area and who do not have English as a native language, must document
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using Python, R, Matlab, Julia or similar is required. Knowledge of energy systems, energy system modelling or the European energy market will be an advantage. Understanding of atmospheric processes