Summary
Lund University is seeking a Postdoctoral Fellow for a two-year research position focused on the modeling of bioaerosols, layer-clouds, and climate dynamics using AI methodologies. This position involves innovative research in a collaborative environment, addressing critical aspects of cloud formation and the role of biological aerosols in climate.
Postdoctoral Fellow in Modeling of Bioaerosols, Layer-Clouds, and Climate with AI, Lund, Sweden
Designation
Postdoctoral Fellow
Job Details
| Category | Details |
|---|---|
| Research Area | Bioaerosols, Climate Sciences |
| Location | Lund, Sweden |
| Employment Type | Full-time, Fixed-term (2 years) |
| Reference Number | PA2026/1176 |
Eligibility/Qualification
- PhD degree in meteorology or equivalent.
- BSc in physics or equivalent.
- Proficiency in English (oral and written).
- Experience in programming within a Linux environment using Fortran and Python.
- Background in numerical modeling, AI, and meteorology is advantageous.
Job Description
The selected candidate will:
- Simulate layer-cloud cases observed in the USA using cloud models and compare with coincident observations.
- Analyze the impact of different bioaerosol types on cloud properties, utilizing an established biological ice nucleation scheme.
- Investigate the relationship between bioaerosols and clouds on a global scale using both conventional and AI-focused modeling approaches.
- Collaborate with a team of atmospheric modelers at the Department of Earth and Environmental Sciences.
How to Apply
Candidates must submit a PDF file including:
- CV with a list of publications.
- A detailed description of past research and future interests (max three pages).
- Contact information for at least two references.
- Copy of doctoral degree certificate and relevant educational credentials.
Applications should be sent using the designated application portal on the Lund University website.
Last Date to Apply
May 13, 2026
This post is designed to attract qualified candidates to an impactful research position, contributing to advancements in climate science through innovative modeling techniques.
