Spontaneous Application - Research Scientist (Core AI or AI for Science)

Join Sigma Nova, a pioneering company focused on building foundation models for science. We are seeking exceptional research scientists in two main profiles: Core AI Researchers and AI for Science Researchers. This is a proactive pipeline building opportunity for potential hires in late 2025 or early 2026.

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Job summary
Permanent contract
Paris
A few days at home
Salary: Not specified
Experience: > 5 years
Education: PhD or more
Skills & expertise
Deep learning
Collaboration and teamwork
Foundation
Key missions

Contribuer à la recherche et au développement de modèles fondamentaux pour la science, en mettant l'accent sur des domaines tels que le cerveau, la biologie, le climat et la physique.

Participer à la conception de nouveaux objectifs d'entraînement, à l'amélioration des architectures de modèles et à l'intégration de l'IA moderne dans des domaines scientifiques.

Collaborer avec des équipes de recherche pour développer des composants de modèles qui ont été adoptés dans des systèmes réels ou des piles de recherche.

Sigma Nova
Sigma Nova

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Questions and answers about the job

The position

Job description

This is not a live opening, but part of our proactive pipeline building.
We’re looking to meet exceptional scientists and elad scientist ahead of potential hires in late 2025 or early 2026.

This page outlines the types of research profiles we’re excited to meet, not a fully scoped role.

Sigma Nova, we’re building foundation models for science—starting with the brain, and expanding into new domains like biology, climate, and physics.

To do that, we are always on the lookout for deep research talent, typically falling into one of two archetypes.



Preferred experience

Profile 1 — Core AI Researchers

You’re a deep learning scientist working on core generative modelling, RL, representation learning, or scalable architectures. You enjoy designing new training objectives, pushing the limits of transformer variants, or working with complex temporal or multimodal data. You likely have a strong publication record and experience developing new model components that have been adopted in real systems or research stacks.

Your past work might include:

  • Diffusion models, score-based generative methods, or GANs

  • Foundation model design (attention mechanisms, tokenisation, scaling laws)

  • Long-context or irregular time series modelling (e.g., EEG, spatiotemporal data)

  • Reinforcement learning or decision-making frameworks


Profile 2 — AI for Science Researchers

You’re a scientist who has integrated modern AI into a scientific domain—be it physics, chemistry, climate, neuroscience, or another field. You’ve either built domain-specific deep learning models or adapted frontier architectures to simulate or explain natural phenomena. You’re fluent in both theory and application, and you’ve published in scientific or AI journals.

Your background might include:

  • Molecular modelling, simulation surrogates, physics-informed ML, or brain modelling

  • Training GNNs, transformers, or diffusion models on scientific data

  • Scientific computation with a data-centric, generative, or learning-based twist

  • Collaborations in academia, specialised startups, or big tech research teams


Recruitment process

We’re currently not actively hiring, but want to engage with researchers who see themselves thriving in this kind of environment. Our next wave of hires may begin in early 2026, with some flexibility for exceptional fits.

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