Fully Funded PhD: Geometry-Driven AI for Multimodal Models

Karlstad University; Torino; In loco; EUR 50.000 - 70.000; Tempo pieno

Descrizione del lavoro

An innovative research institute in Torino is offering a fully funded PhD position focusing on geometry and physics-based inductive biases for foundational models. Candidates should possess an excellent Master’s degree in computer science or a related field, along with a strong background in machine learning, programming skills in Python, and fluency in English. This role involves conducting research and publishing findings while collaborating with interdisciplinary teams. Applications are managed by a partner university.

Servizi

Access to high-performance computing resources

Financial support for attending conferences

Dynamic and interdisciplinary research environment

Competenze

• Must have skills in computer science or related field.
• Background in machine learning and robotics necessary.
• Fluency in English required for communication.

Mansioni

• Conduct research on Riemannian embeddings and curvature-based attention mechanisms.
• Develop and evaluate geometry- and physics-based models.
• Publish findings in peer-reviewed journals.

Conoscenze

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

Team player, but able to work autonomously

Experience with scientific writing

Formazione

Master’s degree

Descrizione del lavoro

An innovative research institute in Torino is offering a fully funded PhD position focusing on geometry and physics-based inductive biases for foundational models. Candidates should possess an excellent Master’s degree in computer science or a related field, along with a strong background in machine learning, programming skills in Python, and fluency in English. This role involves conducting research and publishing findings while collaborating with interdisciplinary teams. Applications are managed by a partner university.