PhD Position – Scalable AI and Advanced Computing for Earth Ob...
Core
Design and adapt AI methods and workflows to handle large, heterogeneous Earth Observation (EO) tasks efficiently and reliably, balancing predictive performance, computational efficiency, and scalability.
Role type
PhD researcher (AI/ML for Earth Observation)
Builds
Reproducible data and experimental workflows, MLOps pipelines, and research prototypes for EO applications. (via careerplan.io/jobs/19380-qhasujlcuc-S-phd-position-scalable-ai-and-advanced-computing-for-earth-ob-at-forschungszentrum-julich-g)
Domain
Earth Observation, Climate Science, Forestry, Agriculture, High-Performance Computing (HPC)
Deliverable
research
Required skills
Machine learning, Deep learning, Python programming, Linear algebra, Probability, Optimisation, Data analysis
Preferred skills
Geospatial data analysis, Parallel/distributed computing, GPU programming, Linux, Containerisation, Quantum computing, Agentic AI
Technologies
PyTorch, TensorFlow, GPU-accelerated computing systems
Responsibilities
Review scientific literature and formulate research questions; Develop and investigate 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
