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Skills you'll use
What you'll do
- Conduct structured literature surveys on deep learning, multimodal learning and remote sensing
- Reproduce and benchmark recent research papers on EO and SAR datasets
- Train, fine-tune and evaluate deep learning models on proprietary satellite imagery
- Design and execute rigorous experiments with proper tracking, ablations and analysis
- Develop architectures including CNNs, Vision Transformers, diffusion models and GANs
- Analyse model performance, identify failure modes and propose improvements
- Collaborate with researchers, present findings and contribute to research publications
Who can apply
- Strong Python and PyTorch skills
- Solid foundations in deep learning and modern computer vision
- Experience with Transformers, generative models (Diffusion, GANs, VAEs) or Vision-Language Models
- Familiarity with Linux, Git and GPU-based training workflows
- Good to have: EO/SAR or geospatial datasets (Sentinel-1/2, Landsat, BigEarthNet), CLIP/BLIP/LLaVA, GDAL/rasterio, MLflow or Weights & Biases
Perks & benefits
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