Analytic Learning Algorithm Researcher (Remote, Portugal)

About the role

We are seeking a researcher to advance analytic learning algorithms that combine probabilistic modeling with rigorous mathematical foundations. The role is fully remote, collaborating with a distributed, CET‑aligned team on high‑impact projects in finance, scientific discovery, and quantitative analysis.

Key responsibilities

• Develop numerical and analytical models for modular probabilistic learning systems.
• Design, analyze, and prove properties of learning algorithms ensuring theoretical soundness.
• Translate academic concepts into implementable code and system components.
• Conduct rigorous experimental evaluations to validate algorithmic performance.
• Write clean, well‑documented code for research experiments and production‑aligned prototypes.
• Collaborate with fellow researchers to integrate insights across domains.

Required profile

• Advanced degree (PhD preferred) in Mathematics, Computer Science, Statistics or a related quantitative field.
• Strong background in mathematical analysis methods such as optimal transport, information geometry, or continuous optimization.
• Research‑oriented mindset with excellent analytical thinking and communication skills.

Required skills

• Probabilistic graphical models (e.g., factor graphs).
• Tractable density estimation techniques: normalizing flows, autoregressive models, probabilistic circuits.
• Mathematical analysis methods: optimal transport, information geometry, continuous optimization.

What we offer

• Fully remote work within a globally distributed, research‑focused team.
• Opportunity to tackle cutting‑edge theoretical problems with real‑world impact.
• High autonomy in a flat, collaborative environment.
• Exposure to interdisciplinary applications across finance, physics and more.