PhD Position – Scalable AI and Advanced Computing for Earth Ob...
Core
Develop and evaluate AI methods and workflows for handling large, heterogeneous Earth Observation (EO) tasks efficiently and reliably using high-performance and cloud computing environments.
Role type
PhD Researcher (AI/EO/Advanced Computing)
Builds
Reproducible data and experimental workflows, MLOps pipelines, and research prototypes for EO applications.
Domain
Earth Observation, Climate Science, Forestry, Agriculture, High-Performance Computing (HPC)
Deliverable
production ML models | research
Required skills
Machine learning, Linear algebra, Probability, Optimisation, Python programming, Deep learning frameworks (PyTorch/TensorFlow), GPU programming, Distributed computing, Data analysis
Preferred skills
EO or geospatial data analysis, Quantum computing, Agentic AI, Open-source contributions
Technologies
PyTorch, TensorFlow, Linux, Containerised environments, GPU-accelerated systems
Responsibilities
Review scientific literature and formulate research questions, Develop AI methods for multisource EO data, Design reproducible data and experimental workflows, Investigate MLOps pipelines for scalable training and inference, Benchmark approaches against established methods, Collaborate with domain researchers to validate methods and integrate prototypes, Publish findings in journals and conferences
Seniority
PhD Candidate (Researcher)
