Research Scientist (AI) – Biomedical Imaging
Palo Alto, CA /
Paris
Engineering /
Full Time /
On-site
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Palo Alto, CA
Paris
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within 1 month after offer signed
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3-6 months after offer signed
Biomedical Imaging
What is your experience level with training Vision Transformers (ViTs) or related transformer-based architectures for imaging tasks?
Advanced – I have trained Vision Transformers or hybrid CNN-Transformer architectures on real-world or biomedical datasets, optimized performance, and evaluated downstream tasks such as classification, segmentation, or embedding extraction.
Intermediate – I’ve fine-tuned or adapted pretrained ViTs for specific tasks using standard libraries (e.g., timm, HuggingFace) but haven’t trained them from scratch.
Beginner – I’ve experimented with ViTs in research or coursework settings but haven’t used them in practical or high-scale applications.
No experience – I have not worked with Vision Transformers.
What is your experience level with self-supervised learning (SSL) techniques for visual or biomedical imaging data?
Advanced – I have developed or applied self-supervised methods (e.g., SimCLR, BYOL, MAE) for vision tasks and evaluated them in real-world or research settings, including on biomedical images.
Intermediate – I’ve implemented SSL models using existing libraries or adapted pretrained models for downstream tasks but didn’t design or train novel approaches.
Beginner – I’ve read about or lightly explored SSL methods in tutorials or academic contexts, but not applied them in practice.
No experience – I have not worked with self-supervised learning.
What is your experience level with image generation using deep learning (e.g., GANs, diffusion models, or autoregressive models)?
Advanced – I’ve trained or fine-tuned generative models (e.g., GANs, VAEs, diffusion) for image synthesis or translation tasks, and evaluated generation quality and model stability.
Intermediate – I’ve used pre-trained generative models or modified architectures but have not trained from scratch or optimized generation quality.
Beginner – I’ve run demos or basic image generation experiments (e.g., Stable Diffusion, StyleGAN) but not in a research or production setting.
No experience – I have not worked on image generation models.
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