The overall objective of this project is to develop better statistical methods for trustworthy evaluation of cancer treatments from registry data in order to support decision makers when forming official clinical guidelines. We use tools from survival analysis, causal inference and stochastic calculus. This particular work package is expected to involve particular techniques from the theory of stochastic differential equations, so the ideal candidate should have some experience with Ito-integrals, martingales etc

Requirements:

Phd degree or equivalent in statistics or mathematics with emphasis on stochastic processes and causal inference; Interest in developing methods for applied problems; Good programming skills (in R, Matlab, Python, C++ or similar). Experience with analyzing large datasets or registry data is an advantage, but not necessary; Fluent oral and written communication skills in English

Text:

Postdoc position in biostatistics/stochastic processes The overall objective of this project is to develop better statistical methods for trustworthy evaluation of cancer treatments from registry data in order to support decision makers when forming official clinical guidelines. We use tools from survival analysis, causal inference and stochastic calculus. This particular work package is expected to involve particular techniques from the theory of stochastic differential equations, so the ideal candidate should have some experience with Ito-integrals, martingales etc Phd degree or equivalent in statistics or mathematics with emphasis on stochastic processes and causal inference; Interest in developing methods for applied problems; Good programming skills (in R, Matlab, Python, C++ or similar). Experience with analyzing large datasets or registry data is an advantage, but not necessary; Fluent oral and written communication skills in English

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