Exposome Bioinformatician — Data Pipelines & Health Insights

Barcelona Institute for Global Health (ISGlobal); Barcelona; On-site; EUR 40,000 - 70,000; Full time

Job summary

ISGlobal, the Barcelona Life Study Cohort (BiSC) project, seeks a motivated bioinformatician to analyze chemical exposome data and relate it to cardiovascular and neurological health outcomes. You will implement novel outcome-wide exposome methods using the msRRR package.

The role offers the chance to contribute to a high-impact international project at the forefront of exposome science, with responsibilities spanning data analysis, pipeline development in R or Python, and result documentation.

Qualifications

• PhD in epidemiology, public health, biostatistics, data science, environmental health, or a related field.
• Proven experience coordinating scientific or research projects, preferably international/multi-cohort.
• Proficiency in R and/or Python for data processing, statistics, and visualization.
• Strong understanding of exposome concepts, longitudinal data, and meta-analysis is a plus.
• Familiarity with exposome tools and platforms (Molgenis, FAIR principles) is an asset.

Responsibilities

• Data analysis and methodological work.
• Develop and implement analytical pipelines in R or Python for chemical exposome data with multiple outcomes.
• Document and interpret results in a structured and reproducible manner.
• Collaborate with cross-disciplinary teams to ensure robust analyses.

Skills

Excellent writing

Organizational skills

Interpersonal skills

Proactive learning

Teamwork

Problem solving

Education

PhD (epidemiology/public health/biostatistics/data science/environmental health)

Tools

R

Python

Molgenis

FAIR principles

Job description

ISGlobal, the Barcelona Life Study Cohort (BiSC) project, seeks a motivated bioinformatician to analyze chemical exposome data and relate it to cardiovascular and neurological health outcomes. You will implement novel outcome-wide exposome methods using the msRRR package.

The role offers the chance to contribute to a high-impact international project at the forefront of exposome science, with responsibilities spanning data analysis, pipeline development in R or Python, and result documentation.