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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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etiology and to maintain a high level of statistical and machine learning competence with focus on image analysis. What do we offer? Choose to work at KI-Ten reasons why Career support for doctoral students
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functions. Other responsibilities include development of methodology and work routines, literature review, statistical analysis, adhering to the lab policies, assisting with administrative tasks and drafting
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degree/ master degree in statistics or biostatistics, or in Health Economics, and ideally previous experience in epidemiological research. Demonstrable advanced skills and expertise in R programming, STATA
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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
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knowledge on cancer etiology and to maintain a high level of statistical and machine learning competence with focus on image analysis. What do we offer? Choose to work at KI-Ten reasons why Career support for
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, or a related field is required. Strong analytic skills and knowledge of statistical programing in SAS or R is also highly desirable. Additionally, the incoming student must have very good command
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regression modeling of survival data, as the project involves development of statistical methodology. Good programming skills in Stata, SAS or R is an advantage. Additional requirements: Excellent