Postdoc: Aerobiological Modeling & Bioaerosol Dynamics

Technical Sciences - Institut for Miljøvidenskab

Roskilde

On-site

DKK 500,000 - 650,000

Full time

4 days ago
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Job summary

Aarhus University invites applications for a 2-year PostDoc in aerobiological modelling, focusing on atmospheric bioaerosols, pollen and fungal spores, and the development of WRF-Chem with Python-based ML components.

The successful candidate will work within the Department of Environmental Science, collaborate with an interdisciplinary team, access leading data streams (Poleno Jupiter, DNA and Hirst-based observations), and contribute to international publications.

Qualifications

  • PhD in environmental science, physics, chemistry, mathematics, engineering or similar.
  • Experience collaborating and presenting at international conferences; lead manuscript authorship.
  • Strong understanding of atmosphere and its modelling.
  • Proven Linux and high-performance computing experience is expected.

Responsibilities

  • Advance development of the WRF-Chem model for bioaerosols, pollen, and fungal spores.
  • Integrate near real-time data into WRF-Chem and related models.
  • Develop Python-based ML models using Poleno Jupiter data and DNA data.
  • Collaborate with an aerobiological group and technicians; disseminate results through papers and conferences.
  • Publish as co-author or lead author in international journals.

Skills

Collaboration experience
Conference presentations
Lead author manuscripts
English fluency

Education

PhD in environmental science, physics, chemistry, mathematics, engineering or similar

Tools

FORTRAN
C
Linux
Python (PyTorch/TensorFlow)
HYSPLIT
WRF-Chem

Job description

Aarhus University invites applications for a 2-year PostDoc in aerobiological modelling, focusing on atmospheric bioaerosols, pollen and fungal spores, and the development of WRF-Chem with Python-based ML components.

The successful candidate will work within the Department of Environmental Science, collaborate with an interdisciplinary team, access leading data streams (Poleno Jupiter, DNA and Hirst-based observations), and contribute to international publications.

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