Research Scientist: Multimodal Foundation Models for Brain Signals

Sigma Nova; Paris; In loco; EUR 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Sigma Nova in Paris is building foundation models for complex scientific signals, starting with EEG, fMRI, and ultrasound, with the aim to extend to other data-scarce domains. The role emphasizes architecture-level thinking, pre-training strategies, and multimodal alignment in a collaborative team.

As a key contributor, you will own experiments from hypothesis to deployment, contribute to engineering pipelines, and advance scientific understanding of physical signals while thriving in an open,

Competenze

• PhD (preferred) in Machine Learning, Deep Learning, or a closely related quantitative field.
• Strong proficiency in PyTorch and experience running large models on GPU infrastructure.
• Hands-on experience handling challenging data, including irregular time series and scientific signals.
• Data-first mindset prioritising raw signals and data quality over loss curves.
• Ability to thrive in ambiguous environments and explain research to non-scientific teams.
• Fluent English.

Mansioni

• Architecture-level thinking: address why standard methods fail on irregular, noisy, or scarce data.
• Develop pre-training strategies tailored to physical signals with small samples.
• Pursue multimodal alignment to bridge gaps between signals and inductive biases for physical systems.
• Take end-to-end ownership: design experiments from hypothesis to deployment and contribute to pipelines.

Conoscenze

PyTorch

Large models

GPU infrastructure

Time-series data

Multimodal alignment

Formazione

PhD (preferred) in ML/DL or related field

Descrizione del lavoro

Sigma Nova in Paris is building foundation models for complex scientific signals, starting with EEG, fMRI, and ultrasound, with the aim to extend to other data-scarce domains. The role emphasizes architecture-level thinking, pre-training strategies, and multimodal alignment in a collaborative team.

As a key contributor, you will own experiments from hypothesis to deployment, contribute to engineering pipelines, and advance scientific understanding of physical signals while thriving in an open,