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# Machine Learning Scientist

- **Company:** Noïa Labs
- **Location:** Paris, France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Machine Learning, Tensorflow, Pytorch, Deep Learning, Model Validation, Generative AI, Information Technology, Decoding
- **Published:** June 5, 2026
- **Apply:** https://fr.indeed.com/viewjob?jk=eafae79c7f10614d

## About the Role

Do you have a Doctoral degree?, * 5+ years of experience in machine learning research, applied ML research, or a related field

 * PhD, MS, or equivalent research experience in machine learning, computer science, computational neuroscience, applied mathematics, physics, electrical engineering, or a related field
 * Strong experience with deep learning for time-series, sequential, multimodal, or sensor data
 * Strong experience with PyTorch, JAX, TensorFlow, or similar frameworks
 * Strong understanding of representation learning, self-supervised learning, transformers, generative models, or foundation models
 * Experience designing rigorous ML experiments, benchmarks, ablations, and evaluation protocols

## Description

We are seeking a talented Machine Learning Scientist to develop the modeling approaches behind our non-invasive neural interface. You will work on learning from neural and multimodal time-series data to help infer human intent and enable new forms of interaction with AI systems. This is a hands-on research role for someone who enjoys developing new ML methods, running rigorous experiments, and turning promising ideas into working prototypes.

The role spans representation learning, self-supervised learning, neural decoding, model evaluation, personalization, and real-time adaptation, while working closely with ML engineers, neuroscientists, software engineers, and product teams.

In this role, you will

 * Develop new machine learning approaches for neural and multimodal time-series data
 * Design experiments, benchmarks, and ablations to evaluate model performance, robustness, and generalization
 * Translate research ideas into working prototypes that can be tested on real data and in user studies
 * Collaborate with BCI scientists and ML engineers to turn neuroscience-informed modeling ideas into reliable training and inference workflows.


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