Health Impact & Burden Modelling Scientist

Barcelona Institute for Global Health (ISGlobal); Barcelona; Presencial; EUR 42.000 - 58.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

36 days off per year (23 vacation days

13 personal days)

Descripción de la vacante

ISGlobal invites applications for a modeller to support quantitative analyses and health impact assessments using datasets from Spanish authorities. The role focuses on burden of disease, health impact modelling, and environmental exposure modelling in urban contexts, with expertise in GBD methodologies.

The candidate should have a PhD in Public Health (or closely related field) and extensive experience in managing large datasets, R/Python programming, and communicating results to diverse

Formación

• Experience in quantitative data analysis and conducting health impact (HIA) and burden of disease assessments.
• Proficient in managing and analyzing large datasets.
• Excellent command of English, both written and oral.

Responsabilidades

• Conduct quantitative analyses, including health impact assessments (HIA) and burden of disease evaluations.
• Collaborate closely with colleagues on the development and management of studies and datasets, performing rigorous statistical, HIA and burden of disease analyses.
• Engage with stakeholders, authorities and peer researchers, and contribute to dissemination of research findings to ensure accessible results.

Conocimientos

Teamwork

Problem resolution

Learning capacity

Educación

PhD in Public Health or closely related field

Herramientas

R

Python

Descripción del empleo

ISGlobal invites applications for a modeller to support quantitative analyses and health impact assessments using datasets from Spanish authorities. The role focuses on burden of disease, health impact modelling, and environmental exposure modelling in urban contexts, with expertise in GBD methodologies.

The candidate should have a PhD in Public Health (or closely related field) and extensive experience in managing large datasets, R/Python programming, and communicating results to diverse