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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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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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experience with designing experimental studies and analysing quantitative data. Proficiency in either R or Python. Favourable qualifications (not requirements, but give applicants an advantage): Relevant
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criteria for the position. Preferred selection criteria Familiar with SPSS, STATA, R, or Python for quantitative analysis Knowledge of NVivo or Atlas.ti for qualitative data analysis Personal characteristics
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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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for this position. Applicants should be proficient in R, Python, or equivalent statistical software. Some background knowledge in either (computational) Bayesian methods, or statistical learning for molecular data
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, biostatistics or similar Experience with handling of large-scale human genotype and registry data (quality control and analysis) Skills in programming and scripting languages (Python/R/Matlab) Fluent oral and
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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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supervised by Professor Amir R. Nejad and your immediate Line Manager is Head of the Department. Duties of the position Development of integrated condition monitoring system from contact less sensor data