Postdoctoral Fellow in causal inference and stochastic processes (ref no 2017/9964)
The clinical health registries in the Nordic countries contain detailed information on individual health histories that provides an opportunity to identify improvements of treatments, or even guidelines, in health care. Applying traditional statistics for this purpose may lead to erroneous conclusions when not distinguishing statistical associations and causal effects. Causal inference combines statistics and mathematical modeling to squeeze out the available information on causal effects from such non-experimental data. The current project aims to develop new methodology for causal inference that is suitable for registry data and observational data from clinical studies. The successful postdoc candidate will develop new statistical methodology, exploiting the unique possibilities offered by the national health registries and other sources of data.
For more information and how to apply: https://www.jobbnorge.no/ledige-stillinger/stilling/141674/postdoctoral-fellow-in-causal-inference-and-stochastic-processes
This job comes from a partnership with Science Magazine and