Bivwac

Building Immersive Visualizations for Welfare, Awareness, and Comprehension

Open Positions

The Bivwac lab is currently looking for talented and motivated PhD students in human-computer interaction and visualization to start in the fall or winter of 2026.

General Info About PhD Positions

Background on Bivwac and Inria

Bivwac is a joint lab between Inria (the French national institute for research in computer science), and CNRS (French National Centre for Scientific Research). It is part of the Inria centre at the University of Bordeaux. Inria is a pure research institution but is affiliated to the University of Bordeaux, which delivers PhD degrees, and where PhD students can engage in optional teaching and undergraduate student supervision.

At Bivwac, we study new forms of immersive and interactive visualization experiences aimed at improving the understanding of complex data and phenomena, often in societal contexts. The objective is to build and study tools that help transmit and advance knowledge in order to promote the building of a sustainable and desirable future.

Funding

Some of the positions listed below are already funded, others are awaiting funding, or require candidates to enter the competition for doctoral school funding.

Across all projects, we will work around the following methods:

Expected profiles for all topics

Desired profiles for some of the topics:

How to apply:

Send an email to phd-26_bivwac@inria.fr with a CV and a letter of motivation in PDF format specifying the research or topic(s) you are interested in, and why. We will be considering applications and conducting interviews during the period of March 23rd to April 24th.

Open PhD topics

[PhD 1] Immersive Data-Driven Storytelling

Keywords: AR, XR, data-driven storytelling, geo-spatial data

Advisors: Benjamin Bach and Martin Hachet

Abstract: This topic investigates data-driven storytelling in data-rich environments such as a digital-twin of the French territory. Digital twins are virtual environments representing and integrating data about real-world phenomena such as the impact of climate change, population demographics, or the distribution of public services. The specific digital twin is a collaboration between different French research institutions and organizations with the goal of making data accessible and usable by wider audiences. This topicx will investigate questions related to the visualization and explanation of these data to people unfamiliar with the phenomena and data as well as the technical immersive environments [1]: how to represent and explain data in immersive environments? how to onboard and familiarize people with these environments? how to interactively discover data? The topic will co-design, develop, and evaluate novel techniques for data-driven storytelling [2] and explanation.

Expected profile: We seek candidates from computer science, design or cognitive science who with strong interests in interdisciplinary and human-centered research. The candidate is expected to bring basic experience in one or more of the following fields: visualization design, virtual and mixed reality, human-subject studies and general methods in human-computer interaction. Applicants should be capable of programming experimental and interactive systems as well as quantiative data analysis. Strong proficiency in required in English (reading, discussions, writing). French is not a requirement but will help with paperwork and daily life.

[1] Méndez, J., Luo, W., Rzayev, R., Büschel, W., & Dachselt, R. (2025). Immersive data-driven storytelling: Scoping an emerging field through the lenses of research, journalism, and games. IEEE Transactions on Visualization and Computer Graphics, 31(10), 6839-6851.

[2] Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE transactions on visualisation and computer graphics, 16(6), 1139-1148.

Funding status: Fully secured.

[PhD 2] Understanding Collective Learning with Data

Keywords: Information visualization, collective learning, social cognition, vicarious learning, human-computer interaction, cognitive psychology

Advisors: Pierre Dragicevic, Yvonne Jansen, Barbara Tversky, François Ric

Abstract: This PhD project will investigate how people understand and learn from data in shared contexts. While most research focuses on individuals, real-world data use typically involves experiencing information collectively, interacting with others. The project will analyze how social settings affect comprehension, engagement, and decision-making with visualizations. Combining perspectives from psychology and human-computer interaction, the research project will examine both traditional and novel forms of data representation, including interactive and physical systems. The goal is to better understand the cognitive and social processes involved in collective data use in order to inform the design of visualization tools that support more effective group understanding.

Expected profile: We seek candidates from computer science or cognitive science who are eager to bridge both fields, with strong English skills and interest in areas like human-computer interaction, visualization, and experimental methods. Applicants should also be capable of programming to build experimental or interactive systems and committed to open science practices. See general criteria here.

Funding status: Not yet fully secured.

[PhD 3] Designing Digital–Physical Collaborative Visualization Environments for Co-Located Collective Decision-Making

Keywords: Collaboration, Shared spaces, Physical installations

Advisors: Martin Hachet and Benjamin Bach

Abstract: This PhD explores digital-physical interfaces and experiences to collaborative visualize, explore, and debate data [1]. Complex data about wicked societal problems, such as climate change, require novel and effective means for diverse audiences to engage with the data; they need to understand the origin of the problem and devise potential solutions all while respecting each other values, opinions, and expertise. In this project, we co-design, develop and evaluate novel interfaces at the intersection of tangible interfaces, interactive visualizations, and data physicalizations to promote collaboration [2] for understanding, exploration, education, debate, and decision making. The topic investigates questions related to novel designs for such interfaces, their efficiency, onboarding and storytelling mechanisms, and to what extend they can support collaboration.

Expected profile: We seek candidates from computer science, design or cognitive science who with strong interests in interdisciplinary and human-centered research. The candidate is expected to bring basic experience in one or more of the following fields: visualization design, virtual and mixed reality, fabrication and tangible interfaces, human-subject studies and general methods in human-computer interaction. Applicants should be capable of programming experimental and interactive systems as well as quantiative data analysis. Strong proficiency in required in English (reading, discussions, writing). French is not a requirement but will help with paperwork and daily life.

[1] Brasier, Eugenie, Yvonne Jansen, Pierre Dragicevic, and Martin Hachet. “Exploring the Feasibility of a Participatory Data Physicalization of CO₂e Emissions for Dietary Choices in Collective Catering Settings.” (2025).

[2] Isenberg, P., Elmqvist, N., Scholtz, J., Cernea, D., Ma, K. L., & Hagen, H. (2011). Collaborative visualization: Definition, challenges, and research agenda. Information Visualization, 10(4), 310-326.

Funding status: Not yet fully secured.

[PhD 4] Cognitive Foundations of Magnitude Visualization

Keywords: Information visualization, visual literacy, numeracy, cognition

Advisors: Yvonne Jansen and Pierre Dragicevic

Abstract: This PhD investigates how interactive and embodied representations can improve human understanding of numerical magnitudes that lie outside everyday experience—such as those encountered in scientific, economic, or societal contexts. Despite innate numerical cognition, people often struggle to interpret large-scale or abstract quantitative information, which can impact reasoning and decision-making. The project will explore theoretical and applied methods to design, implement, and evaluate representations that enhance intuitive comprehension. Drawing on cognitive science, information visualization, and human-computer interaction, the work aims to develop evidence-based approaches for communicating complex quantitative data effectively. Suitable for candidates with a background in cognitive science, computer science, or related fields.

Expected profile: We seek candidates from computer science or cognitive science who are eager to bridge both fields, with strong English skills and interest in areas like human-computer interaction, visualization, and experimental methods. Applicants should also be capable of programming to build experimental or interactive systems and committed to open science practices. See general criteria here.

Funding: Doctoral school competition.

[PhD 5] Unconventional Data Visualizations for Insight and Engagement

Keywords: Information visualization, human-computer interaction, graphical perception, mixed reality, animation, user experiments

Advisors: Martin Hachet and Pierre Dragicevic

Abstract: This interdisciplinary PhD thesis focuses on exploring novel approaches to data visualization that go beyond conventional charts and graphs. It investigates how dynamic and immersive visual representations can enhance the way people perceive, understand, and engage with hard-to-grasp quantities, in line with recent work from the team [1, 2]. The work combines principles from perception, design, and human-computer interaction to study how visual experiences influence both intuitive understanding and emotional responses. The student will have the opportunity to experiment with unconventional visualization methods, prototype interactive designs, and contribute to advancing the boundaries of how data can be communicated effectively in both desktop and immersive environments.

Expected profile: The position requires strong English proficiency, solid programming skills, and experience with 3D tools, with XR knowledge as a plus. Candidates should be motivated by multidisciplinary, user-centered work and have an interest in experimental methods and open science practices.

[1] Assor, A., Prouzeau, A., Dragicevic, P., & Hachet, M. (2024). Augmented-Reality Waste Accumulation Visualizations. ACM Journal on Computing and Sustainable Societies, 2(11), 29.

[2] Yang, L., Ferron, A., Jansen, Y., & Dragicevic, P. (2026). Progressive Value Reading: The Use of Motion to Gradually Examine Data Involving Large Magnitudes. arXiv preprint arXiv:2602.19853.

Expected profile: AR and desktop development, user studies, interdisciplinary approach (computer science, psychology, design).

Funding: Doctoral school competition.