As a postdoctoral fellow in epidemiology, you will work in an interdisciplinary team at Uppsala University with extensive experience in bioinformatics, biostatistics and biochemical analyses. The research group has extensive experience applying AI and machine learning methods to analyze biological data (eg proteins and metabolites) in biological samples from different cohorts.
As a postdoctoral fellow, you will work with an overall interdisciplinary approach for a broad project area. You are expected to work both independently and as part of a team. We work with experienced epidemiologists from whom you will receive guidance in your tasks. Within the research group, you will mainly focus on epidemiological questions, which requires the ability to take initiative and to be able to run projects independently.
Within the project, you will perform efficient large-scale data management with great attention to detail. You will also design and develop statistical analysis plans, including advanced methods in epidemiology. Statistical analyses will then be carried out following the statistical analysis plans. A significant part of the work also consists of preparing reports, writing scientific articles, and presenting results at internal and external meetings.
PhD in epidemiology or a foreign degree deemed to be equivalent to a PhD in epidemiology. Depending on the candidate, other subjects for the doctoral degree may also be relevant for the job, such as biostatistics, bioinformatics, computational biology, and public health sciences. The degree must be completed at the latest at the time when the employment decision is made. Primarily, those who have completed their degree no more than three years ago should be considered. When calculating the time frame of three years, the starting point is the application deadline. For special reasons, such a degree may have been completed earlier. Special reasons refer to leave due to illness, parental leave, positions of trust within trade unions, etc.
Great importance will be placed on scientific skills such as research profile, experience, and knowledge, as well as personal qualities such as good collaboration skills, motivation, and independence, as well as how the applicant is judged to have the abilities required for the position through his previous experiences and competencies.