Research Intern in Atmospheric Jet Variability

Position Overview

We are looking for one full-time research intern who will be working on large-scale atmospheric circulation. The intern will investigate the dynamics of the mid-latitude jet and storm track, and how these systems respond to anthropogenic climate change.

This project encompasses data analysis and numerical simulations. Importantly, the position requires the application of advanced data analysis tools and cutting-edge machine learning techniques to analyze large-scale climate data. Familiarity with machine learning, climate modeling, and/or geophysical fluid dynamics is preferred but not mandatory.

The position is for six months, with the possibility of converting to a one-year full-time research fellow.

Reports to

Ding Ma, Assistant Professor of Atmospheric and Environment Science

Essential Duties

• Analyze large datasets (e.g., ERA5, CMIP6) to study atmospheric jet variability using conventional statistical analysis and cutting-edge machine learning techniques.
• Write manuscripts for scientific journals.

Required Qualifications

• A senior undergraduate or master student in Atmospheric Science, Physics, Data Science, or a closely related field.
• Proficiency in programming languages commonly used in climate science (e.g., Python and Fortran). Experiences with climate simulations and Unix/Linux environment.
• Good writing skills in English. Ability to independently complete literature reviews and draft scientific reports.
• Availability to work on-site 5 days a week, six months (from 1 March to 31 Aug 2026).

Preferred Qualifications:

• Experiences with pattern recognition and/or state-space modelling.
• Background in mid-latitude dynamics and annular modes; familiarity with jet/storm-track diagnostics and eddy–mean flow interaction.

Application Materials:

• CV, cover letter, and contact information for 1 reference.
• Optional: a link to a code repository (e.g., GitHub).