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

About the role

The RCLN team is offering a research internship focused on Machine Learning and Natural Language Processing. Interns will explore classic latent-variable models through modern approaches such as Variational Autoencoders (VAEs) and diffusion processes, aiming to advance state‑of‑the‑art NLP techniques.

Key responsibilities

• Conduct a literature review of historical latent‑variable models and recent VAE/diffusion methodologies.
• Design and implement experimental pipelines using VAEs or diffusion processes for NLP tasks.
• Evaluate model performance on benchmark datasets and analyze results.
• Collaborate with team members to document findings and prepare research reports.

Required profile

• Currently enrolled in a graduate program (Master's or PhD) in Computer Science, Machine Learning, or a related field.
• Strong interest in research on generative models and natural language processing.
• Ability to work independently and communicate research outcomes effectively.

Required skills

What we offer

• Hands‑on experience with cutting‑edge generative modeling techniques.
• Opportunity to contribute to publishable research.
• Mentorship from experienced researchers in the RCLN team.