Postdoc: Bayesian Networks for Environmental Health Impact

DTU - Technical University of Denmark; Kongens Lyngby; On-site; DKK 450,000 - 600,000; Full time

Job summary

DTU National Food Institute seeks a postdoctoral researcher to develop quantitative weight-of-evidence approaches based on Bayesian networks for environmental burden of disease studies. The role focuses on integrating evidence from toxicology and epidemiology to evaluate health impacts of environmental chemicals, with a PFAS case study.

The ideal candidate holds a PhD in statistics or related fields, has experience with Bayesian methods, and excels in interdisciplinary teamwork and rigorous,

Qualifications

• PhD required in statistics, biostatistics, mathematics, data science, ML, systems biology, quantitative epidemiology, or related field.
• Experience with Bayesian methods and Bayesian networks.
• Strong analytical, problem-solving and communication skills in English.

Responsibilities

• Research on Bayesian networks to integrate diverse evidence in environmental burden of disease assessments.
• Develop quantitative weight-of-evidence framework accounting for uncertainty.
• Publish in peer-reviewed journals and present at international conferences.
• Collaborate with project partners and organize virtual meetings.

Skills

Bayesian methods

Bayesian networks

Analytical skills

Independence

Education

PhD in statistics or related field

Job description

DTU National Food Institute seeks a postdoctoral researcher to develop quantitative weight-of-evidence approaches based on Bayesian networks for environmental burden of disease studies. The role focuses on integrating evidence from toxicology and epidemiology to evaluate health impacts of environmental chemicals, with a PFAS case study.

The ideal candidate holds a PhD in statistics or related fields, has experience with Bayesian methods, and excels in interdisciplinary teamwork and rigorous,