Research Internship: Latent Variable Models for NLP (VAEs/Diffusion)

About the role

The RCLN team is seeking a motivated research intern to explore latent-variable models for Natural Language Processing. The project revisits classic latent-variable approaches through modern techniques such as Variational Autoencoders (VAEs) and diffusion processes, aiming to advance state‑of‑the‑art NLP models.

Key responsibilities

• Review and analyze existing latent-variable models in NLP.
• Design and implement experiments using VAEs and diffusion‑based methods.
• Collaborate with senior researchers to evaluate model performance.
• Document findings and prepare reports or academic papers.

Required profile

• Current graduate or undergraduate student in Computer Science, Machine Learning, or a related field.
• Strong interest in research and ability to work independently.
• Good written and verbal communication skills in English.

Required skills

• Machine Learning fundamentals.
• Natural Language Processing concepts.
• Experience with Variational Autoencoders (VAEs).
• Familiarity with diffusion processes or generative modeling.

What we offer

• Hands‑on research experience in a leading AI lab.
• Mentorship from experienced researchers.
• Opportunity to contribute to publishable work.