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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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promoting diverse talent. Reach out to talent@uq.edu.au for accessibility support or adjustments. Applications close 19 May 2025 at 11.00pm AEST (R-48133). Please note that interviews have been tentatively
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analysis with other complementary methodologies, such as structural MRI/DTI, EEG/ERP, eye tracking, and/or psychophysiology. Scripting and programming skills (e.g., R). Evidence of independence in fMRI
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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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software such as R, MPlus, etc.) 5. Demonstrated experience with dissemination (i.e., writing publications and/or presenting at conferences/workshops) 6. Demonstrated strong verbal and interpersonal
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software such as R, MPlus, etc.) 5. Demonstrated experience with dissemination (i.e., writing publications and/or presenting at conferences/workshops) 6. Demonstrated strong verbal and interpersonal
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 18 hours ago
Police (3) Adv Educ in General Dentistry (2) Advancement (2) Advancement Services (2) Alumni Affairs & Constituent R (2) Athletics (2) Benefits (2) Biochemistry (2) Chemical & Biochemical Engrg (2) Child
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statistical analysis and software (e.g., Stata or R). Have experience with causally focused epidemiological or econometric methods. Demonstrate a track record of attracting research funding. Show commitment