Seeking Incoming Masters and PhD Students — Applied ML, Precipitation, Spaceborne Radar

We are inviting 1-2 incoming Master’s and PhD students to join our group at the intersection of applied machine learning, precipitation science, and spaceborne remote sensing. Our work focuses particularly on snowfall and mixed-phase precipitation, applying modern ML techniques and physical models to address real-world challenges. We are also deeply interested in understanding the structure of machine learning models and how we can improve the trust and transparency of these models in future research.

This is an initial posting that will be updated over time as roles are filled.

Our research themes include:

• Trustworthy AI
  Developing artificial intelligence systems that are reliable, transparent, and fair, helping users understand and trust the models they use.

• Precipitation Modeling
  Creating models that improve how we measure, predict, and understand rain, snow, and other forms of precipitation.

• Physics-Informed ML & Foundation Models
  Designing machine learning methods that combine data with physical laws to make predictions that are both accurate and scientifically sound. We are also interested in investigating the abilities of foundation models for hetrogeneous variables.

• Visualization
  Building tools to explore and explain complex data through clear, interactive visual displays that reveal hidden patterns.

We welcome students from diverse academic backgrounds (e.g., computer science, atmospheric science, physics, remote sensing) and are open to international collaborations. For more information on the application process and admission requirements, please see: https://aos.wisc.edu/academics/graduate/admission/

If you are interested in joining us or collaborating, please reach out via email at fraser.king@wisc.edu with your background, interests, and CV. The priority application deadline is January 1st, 2026.