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PhD-level and masters-level statisticians, and doctoral students. The group is involved in a wide variety of research projects, including the development of statistical methods, population-based cohort
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. The candidate should ideally have some previous experience or education in epidemiology and quantitative data analysis. Demonstrable advanced skills and expertise in statistic programming software as R
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using ImageJ for image analyses and Prism for statistics and data plotting. Previous participation in academic research in this area is a must, as is strong communication skills in English as well as a
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. Skills and personal qualities The candidate must hold a degree in computer science, statistics, mathematics, health data science or related disciplines. Documented experience of data science is required
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, Data Science, Bioinformatics, or related fields. Familiarity with basic concepts of statistical analysis is required. Strong programming skills in Python, R and Linux-based software or similar languages
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at the division. The student will become part of the Clinical Cancer Epidemiology research group at KEP. The research group currently consists of 20 researchers with both medical and statistical backgrounds
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or higher. You will be responsible for performing statistical analyzes regarding the accuracy of the AI algorithms compared to registered cancer diagnoses and compared with the radiologists
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leverage computational methods, statistical models, and machine learning to dissect and interpret vast datasets to uncover novel insights that can lead to improved treatment strategies. Key Responsibilities
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could lower the risk of future outcomes. The goal of this project is to apply multivariate statistics and quasi-causal designs to examine whether various interventions might be causally linked to lower
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differences in occurrence, treatment, and care management of older adults with depression. You will be expected to contribute to study design, carry out statistical analyses, interpretation, and presentation