Large-scale multi-view 3D learning

Position: Research appointment (pre-doc) Institute: Uni. Turin
New! Posted on: 19/03/2026 Deadline: 09/04/2026

Scientific-Disciplinary Group

01/INFO-01 - Informatics

Description

The research activity aims to extend the capabilities of current 3D learning models, such as Gaussian Splatting (GS). GS achieves a highly accurate 3D reconstruction of a single scene from a set of multi-view images. The objective of the project is to generalize 3D learning to larger and multimodal datasets (multi-view images and point clouds), contributing to the development of new foundational 3D rendering models capable of learning and capturing not only geometric properties but also the physical characteristics of a scene. The project includes international collaboration with the Department of Computer Science at Simon Fraser University (Vancouver, Canada).

Compensation

22,500 Euro

Job posting website

https://lavorainateneo.unito.it/index_ir.html?type=SEL_IDR

Number of positions

1

Maximum duration

12.0

Funding body

Università di Torino

How to apply

https://pica.cineca.it/unito/sdn-2026-ii/

Selection process

Click to expand
Based on Qualifications and Interview. The interview schedule is published on the University Albo ( https://webapps.unito.it/albo_ateneo/ ) and on the University website ( https://lavorainateneo.unito.it/index_ir.html?type=SEL_IDR ). Candidates will NOT receive notification of their admission to the interview. The publication of the schedule on the University Albo constitutes legal notification of the interview invitation. Applications must be submitted via the online procedure https://pica.cineca.it/unito/sdn-2026-ii/ — for information: incarichiricerca@unito.it Mandatory requirement for admission to the selection: italian Laurea Magistrale, or Laurea a Ciclo Unico, or an equivalent degree from foreign Universities, obtained no more than 6 years prior to the application deadline (i.e obtained after April 9, 2020). The Call for Applications (published on the University Bulletin Board under ref. no. 2721 del 19/03/2026), containing the procedures to participate in the selection process and the specific requirements for each selection, is available at https://webapps.unito.it/albo_ateneo/ and https://lavorainateneo.unito.it/index_ir.html?type=SEL_IDR .

View the original posting on the MUR website: Go to MUR website

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