PhD Position on Riemannian Geometry in Reinforcement Learning

AI4I; Collegno; In loco; EUR 20.000 - 30.000; Tempo pieno

Descrizione del lavoro

A leading research institute in Italy is seeking a motivated candidate for a fully funded PhD position focusing on Riemannian Geometry in Reinforcement Learning. The ideal candidate should have a strong background in machine learning, robotics, and a good command of Python programming. This role offers the chance to contribute to innovative research addressing complex problems in RL algorithms.

Servizi

Access to high-performance computing resources

Opportunities for international collaboration

Financial support for conferences and schools

Competenze

• Excellent academic background in relevant fields is essential.
• Strong knowledge in machine learning and robotics is required.
• Proficiency in Python programming is expected.

Mansioni

• Explore non-Euclidean geometries for RL algorithms.
• Formulate policy learning methods based on Riemannian geometry.
• Apply developed methods in controlling physical systems.

Conoscenze

Excellent Master’s degree in relevant fields

Strong background in machine learning and robotics

Good programming skills in Python

Fluent in spoken and written English

A team player, but also can work autonomously

Experience with scientific writing

Formazione

Master’s degree in computer science, physics, mathematics, electrical or mechatronics engineering

Descrizione del lavoro

PhD Position on Riemannian Geometry in Reinforcement Learning

AI4I – The Italian Institute of Artificial Intelligence and Università degli Studi di Genova invite applications for a PhD position in Riemannian Geometry in Reinforcement Learning as part of the PhD Programme in Hostile and Unstructured Environments.

Deadline

December 17th 2025 at 12 (noon – CET)

Hosting Institution

AI4I – The Italian Institute of Artificial Intelligence

Department

PHI Lab

Funding Scheme

This doctorate grant is fully funded by AI4I in collaboration with Università degli Studi di Genova.

Position Description

Reinforcement learning (RL) methods have been applied in a broad range of application domains, and represent one of the most successful learning paradigms for fine-tuning modern foundational models. However, most of RL methods work under the assumption that the states, actions and policy belong to Euclidean spaces. This PhD thesis is aimed at exploring how non-Euclidean geometries can be leveraged into the representation of states and actions in RL algorithms, and how such geometries impact the policy learning formulation. The first objective is to relax the Euclidean assumption on the formulation of a general RL problem via a Riemannian perspective. Later, the thesis will explore how methods like policy gradient need to be reformulated accordingly, and which advantages and challenges this new perspective brings in. Moreover, from a top-down approach, the next objective will be to leverage the Riemannian geometry of the Wasserstein space to understand, analyze and formulation policy learning methods based on Riemannian gradient flows and Wasserstein metrics. The thesis will explore applications of the developed methods in the control of physical systems such as robots or quadrotors, as well as the fine-tuning of foundational models, among others.

Requirements

• Must have skills:
  • Excellent Master’s degree in computer science, physics, mathematics, electrical or mechatronics engineering, or a related field
  • Strong background in machine learning and robotics
  • Good programming skills in Python
  • Fluent in spoken and written English
  • A team player, but also can work autonomously
  • Experience with scientific writing
• Good to have skills:
  • Background on (applied) differential geometry
  • Publication of peer-reviewed research papers

References

3.G. Tennenholtz and S. Mannor, “Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning”, NeurIPS, 2022.

Number of Positions Available

1

Application Documents

• One-page cover letter including a short (two-paragraph) research proposal related to the PhD topic and aligned with your professional interests.
• Bachelor’s and Master’s diplomas with transcripts and grades.

Main Research Site

AI4I – The Italian Institute of Artificial Intelligence for Industry

What We Offer

• Access to high-performance computing resources and advanced research infrastructure.
• Opportunities for international collaboration and contributions to high-impact publications.
• A dynamic and interdisciplinary research environment.
• Financial support for attending international conference and Winter/Summer schools.

Start Date

1st March 2026

How to Apply

Please apply via the university’s official PhD admissions portal:

For More Information

https://drim.i-rim.it/en/admission/

About AI4I

AI4I – The Italian Research Institute for Artificial Intelligence has been founded to perform transformative, application-oriented research in Artificial Intelligence.

AI4I is set to engage and empower gifted, entrepreneurial, young researchers who commit to producing an impact at the intersection of science, innovation, and industrial transformation.

Highly competitive pay, bonus incentives, access to dedicated high-performance computing, state-of-the-art laboratories, industrial collaborations, and an ecosystem tailored to support the initiation and growth of startups stand out as some of the distinctive features of AI4I, bringing together people in a dynamic international environment.

AI4I is an Institute that aims to enhance scientific research, technological transfer, and, more generally, the innovation capacity of the Country, promoting its positive impact on industry, services, and public administration. To this end, the Institute contributes to creating a research and innovation infrastructure that employs artificial intelligence methods, with particular reference to manufacturing processes, within the framework of the Industry 4.0 process and its entire value chain. The Institute establishes relationships with similar entities and organizations in Italy and abroad, including Competence Centers and European Digital Innovation Hubs (EDIHs), so that the center may become an attractive place for researchers, companies, and start‑ups.

Seniority level

Entry level

Employment type

Full-time

Job function

Research, Engineering, and Information Technology

Industries

Research Services and Robotics Engineering

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