Doktorand inom Generativ AI & satellitdata för prediktion av urban värme
Core
Developing high-resolution spatiotemporal maps of urban air temperature using conditional diffusion models to fuse satellite, forecast, and crowdsourced station data.
Role type
PhD researcher in deep generative learning and computer vision
Builds
Probabilistic maps of urban air temperature
Domain
Urban climate monitoring, remote sensing, deep generative AI
Deliverable
production ML models
Required skills
deep learning, conditional diffusion models, computer vision, remote sensing, Python, TensorFlow, PyTorch, JAX
Preferred skills
GPU-based experimentation, cluster computing (Docker, Slurm), prior specialization in machine learning
Technologies
TensorFlow, PyTorch, JAX, Docker, Slurm
Responsibilities
Implement and train conditional diffusion models for temperature prediction, fuse heterogeneous data sources (satellite, forecast, crowdsourced), conduct experiments on large-scale datasets
Seniority
PhD candidate (researcher)