Postdoc: Data-Driven Plastic Emissions Modeler

Universität für Bodenkultur; Österreich; Vor Ort; EUR 51.000 - 61.000; Vollzeit

Zusammenfassung

Universität für Bodenkultur Vienna is seeking a highly qualified researcher to develop data-driven and physics-informed models for upscaling micro- and nanoplastic emissions. The role connects laboratory observations with environmental forcing parameters and integrates parameterizations into atmospheric transport models.

The candidate should hold a PhD in a related area, possess excellent English, and have strong programming and data-analysis skills for large-scale environmental datasets.

Qualifikationen

• PhD in environmental modelling or a related field.
• Excellent written and spoken English.
• Experience with scientific programming and large-scale data analysis.
• Strong quantitative and analytical skills.
• Background in atmospheric sciences or related areas.

Aufgaben

• Develop data-driven and physics-informed models to upscale emissions.
• Connect laboratory observations with environmental forcing parameters.
• Integrate emission parameterizations into atmospheric transport models.
• Perform statistical analysis and predictive modelling.
• Synthesize large datasets to constrain marine plastic emission fluxes under realistic ocean conditions.
• Develop and apply upscaling approaches for laboratory measurements to regional/global estimates.
• Collaborate with AERIAL consortium teams across disciplines.
• Disseminate results through publications and meetings.

Kenntnisse

PhD in related field

English proficiency

Scientific programming

Data analytics

Statistics

Quantitative skills

Ausbildung

PhD required

Tools

Python

R

MATLAB

Jobbeschreibung

Universität für Bodenkultur Vienna is seeking a highly qualified researcher to develop data-driven and physics-informed models for upscaling micro- and nanoplastic emissions. The role connects laboratory observations with environmental forcing parameters and integrates parameterizations into atmospheric transport models.

The candidate should hold a PhD in a related area, possess excellent English, and have strong programming and data-analysis skills for large-scale environmental datasets.