The Department of Medical Informatics is looking for six PhD students to work on cutting-edge health data science topics. This research will be performed in close collaboration with the Observational Health Data Sciences and Informatics (
OHDSI) initiative, which is a global, multi-stakeholder, interdisciplinary collaborative to bring out the value of health data through large-scale analytics and the EU-sponsored European Health Data and Evidence Network
(EHDEN) and
eTransafe projects, which develop frameworks to generate reliable real-world evidence.
The PhD students will be responsible for the development and application of novel methods and techniques on data from large Electronic Health Record databases. Research will be performed in natural language processing, feature engineering methods, deep-learning, and other advanced machine-learning methods to support personalized medicine. The PhD students will have the opportunity to develop predictive models and perform validation studies at an unprecedented global scale through the standardization of health data to the OMOP Common Data Model. Impact assessments of these new approaches on patient care are part of the research agenda.