Sofie Theresa Thomsen
2 months ago
This position has expired. You can browse more openings on our positions listing pages.
Postdoc in Bayesian Modelling for Toxicology, Epidemiology, Evidence Synthesis and Burden of Disease at DTU Food Technical University of Denmark in Denmark
Degree Level
Postdoc
Field of study
Epidemiology
Funding
Full funding availableDeadline
Expired
Country
Denmark
University
Technical University of Denmark

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
About this position
DTU Food’s Risk-Benefit Assessment Group is advertising an open 2-year postdoc position focused on Bayesian modelling and its application across toxicology, epidemiology, evidence synthesis, and burden of disease studies.
The group develops models to quantify the health and sustainability impacts of foods, diets, and dietary transitions. This postdoc is a strong fit for candidates with advanced quantitative skills and an interest in food-related health assessment, risk-benefit analysis, and population-level evidence integration.
Institution: Technical University of Denmark (DTU), Denmark.
Eligibility highlights: solid experience in Bayesian modelling; interest in interdisciplinary work spanning toxicology, epidemiology, evidence synthesis, and burden of disease research.
Application: The post links to the DTU Career Site application portal. No deadline was stated in the post content provided. For questions, contact Sofie Theresa Thomsen.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
Official Email
Ask ApplyKite AI
Professors

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.