A Ph.D. student position in Data Mining for Health is open for application at Halmstad University, Sweden.
Apply via: Doctoral student in data mining for health
Application deadline: 25 October 2020
Short Description:
The selected Ph.D. student will carry out research on developing machine learning models, for prognostic purposes, based on individual trajectories of diseases, healthcare contacts, medications, and sociodemographic conditions. The projects will focus on cardiometabolic diseases (including myocardial infarction, acute heart failure, and cardiac death), hospitalization burden (including surgical need and days of hospitalization), and mortality. The follow-up periods range from more than 20 years (Malmö Diet and Cancer Cohort), up to 10 years (Region Halland database) down to 1-2 years in some of the emergency department databases (Lund). The machine learning work will also include developing methods that can explain the decision made by the models (XAI). The selected Ph.D. student will be responsible for conducting research within the AIR Lund project and for participating in the required Ph.D. course activities. The employment also includes teaching responsibilities corresponding to a maximum of 20% of full-time.
This is a full-time position available as soon as possible for a period of four years (extended one year at a time, subject to satisfactory progress of the Ph.D. study). Enough resources to fund experiments and conference travels are available.
