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Field
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proficiency in R or Python for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including
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qualitative methods; some background in or willingness to learn computational social science methods as well as R and/or Python is highly desirable. Willingness to develop an ambitious empirical research
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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longitudinal analyses preferred but not required), including independence with use of SAS, SPSS, and/or R software Ability to efficiently multitask and meet deadlines Skill in taking initiative, assuming
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that provide analysis of both liquids and gasses. The successful candidate is expected to spend approximately 50% of the time at TOPSOE R&D, located in Lyngby. Principal supervisor: Professor Jan H. Christensen
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: Master’s degree in biomedicine or biostatistics. Doctor of medicine degree with clinical practice experience. Certified training in R and Python software. Documented experience using machine learning and
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Familiarity with software such as R or Python Some experience
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, collection and analysis of social media data, experience with R or Stata) is an advantage. For the assessment of personal suitability, we place particular emphasis on good interpersonal skills
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, AquaCrop) or experience with agricultural or environmental modelling. Some experience with programming in R and/or Python. Exposure to climate or weather data, forecasting systems, or geospatial tools
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critical data studies and willingness to reflect on data use and circulation. Demonstrable skills in scientific writing and data analysis. Knowledge of GIS and R and/or Python as a tool for data analysis