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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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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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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
integration, processing, and modeling. Familiarity with research methodologies related to innovation and sustainability. Competence in programming languages such as Python, R, or Stata. Contact information
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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
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employment. Documented knowledge on renewable energy is required. Experience and proven knowledge in scientific programming using Python, R, Matlab, Julia or similar is required. Knowledge of energy systems
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programming language R Fluent oral and written communication skills in English The following qualifications are not required but will give applicants an advantage The quality of the project description and the
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to the contact person no later than June 20th. Advanced quantitative research skills Familiarity with the statistical programming language R Fluent oral and written communication skills in English The following
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. Experience in programming in languages such as MATLAB, R or Python is a requirement. Experience in Magnetic Resonance (NMR, MRS, or MRI) is a requirement. Experience in machine learning and processing
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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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with methods for causal inference Familiarity with administrative register data or other types of big data Familiarity with Stata, R, or other relevant computing languages Personal skills A collaborative