Phd Position F/m Sportsviz: Advanced Situated Visualizations for Sports Videos

_Le descriptif de l’offre ci-dessous est en Anglais_

**Type de contrat**: CDD

**Niveau de diplôme exigé**: Bac + 5 ou équivalent

**Fonction**: Doctorant

**A propos du centre ou de la direction fonctionnelle**:
The Inria Saclay-Île-de-France Research Centre was established in 2008. It has developed as part of the Saclay site in partnership with **Paris-Saclay University** and with the **Institut Polytechnique de Paris**.

The centre has 40 pr**oject teams**, 27 of which operate jointly with Paris-Saclay University and the Institut Polytechnique de Paris; Its activities occupy over 600 people, scientists and research and innovation support staff, including 44 different nationalities.

**Contexte et atouts du poste**:
**Location & Duration**:

- The PhD student will enroll at the Universite-Paris Saclay (12th worldwide in the Shanghai ranking in 2024 and the top ranking French university) in the computer science graduate school. The student will be hosted in the Aviz team at Inria, which is the French national research institute dedicated to digital science and technology.
- Location: Bât 660, Digiteo Moulon, Université Paris-Saclay, 91190, Gif-Sur-Yvette
- The PhD funding is available for a duration of three years. While the previous page lists September as the starting date, the money for the project is available from now and therefore** earlier start dates are possible**.

**Benefits package**:

- Subsidized meals
- Partial reimbursement of public transport costs
- Vacation: around 40 days a year + possibility of exceptional leave (sick children,
- moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer
- equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

** Remuneration**:

- Gross salary : ~2.200 euros/month

**Collaboration**
- The project is part of a nationally funded research project SportsViz in which we collaborate with the Ecole Centrale de Lyon and Inria Grenoble.

**Travel**
- Regular travel is foreseen for this post to present research results and/or talk to athletes or coaches. Travel expenses are covered within the limits of the project.

**Mission confiée**:
This PhD thesis is part of a nationally project in which we aim to improve audience engagement through advanced situated visualizations in sports videos. Specifically, we envision to embed large volume of heterogeneous, performance-related sports data with innovative data visualizations directly into sports videos. While data as visualization have a strong narrative and analytical power for sports analysis they currently are not integrated where and when they are relevant in videos. The standard way scientists or broadcasters display data is using visualizations inserts superimposed on the video rather than situated into the sports 3D scene e. g. on the wall, leveraging the physical context to show the progress, emphasize key performance factors (e. g. forces, speed) and put them in perspective with competitors. The resulting situated visualization would enable an informed decision-making process to make strategic choices, but also would engage a broader audience such as sports fans while preserving and enhancing the viewing experience.

**Principales activités**:
For more details see the project description.

This phd project is part of a project in which we aim to improve audience engagement through advanced situated visualizations in sports videos. Specifically, we envision to use the narrative power of data visualization to engage a broader audience such as sports fans. We ant to show them additional data about athletes of interest while preserving and enhancing their viewing experience.

As part of this research there are multiple possible topics to start with.

**Design oriented**: Situated visualization onboarding. When audiences watch situated visualizations embedded in video online such as for the Olympics (examples here) it is unclear what designs should look like to be read and understood the most easily. This project involved creating and testing multiple design alternatives.-
- **Qualitative research oriented**: Elicit requirements for when and how situated visualizations should appear and disappear in sports videos. Test different alternatives in an online user study. We expect from this line of research to build a series of guidelines on best design practices for situated visualizations.-
- **Perception oriented**: Run perceptual studies with participants to learn how well they are able to read situated visualizations in sports videos. You can compare specific designs according to: how many different types of data viewers can track, what kind of changes they will perceive, or for how long a visualization should be visible to be useful.-
- **User experience evaluation**: Run user experience evaluations with a general population of sports f