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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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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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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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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
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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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to work independently and collaboratively in multidisciplinary teams Desired qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput
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quantitative research skills Familiarity with the statistical programming language R Fluent oral and written communication skills in English The following qualifications are not required but will give applicants
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data Familiarity with Stata, R, or other relevant computing languages Personal skills A collaborative, friendly, and team-oriented style of work Ability to join interdisciplinary academic communities
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modelling. Applicants must have good skills in programming (e.g. Python, R, Java Script) Experience (for example a master project or internship) working with snow or the cryosphere is a requirement
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qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Familiarity with