Master 2 Internship Proposal: Data analysis

Analyzing Gender Inequities in Neuroscience: Comparative Study of the 2022 and 2025 Bordeaux Neurocampus Surveys

Host Institution: Bordeaux Neurocampus

Duration: 6 months (Spring 2026)

Supervision: Amélie Aussel

Context and Objectives

Gender equity remains a critical challenge within academia and research environments, including neuroscience. Following a pioneering gender equity survey conducted in 2022 at Bordeaux Neurocampus —whose results revealed important disparities in perception, experience, and opportunity — an updated survey will be carried out in Fall 2025. The proposed internship aims to analyze the 2025 data and compare it with the 2022 baseline to assess progress, identify persistent gaps, and inform future actions.
The main objectives of the internship are:
• To clean, structure, and statistically analyze the 2025 survey data;
• To compare the 2025 data with the 2022 results (available here: https://www.bordeaux-neurocampus.fr/resultats-de-lenquete-2022-sur-les-inegalites-liees-au-genre/);
• To explore differences across variables such as gender and career stage
• To contribute to a final report and potential communication material for the Neurocampus community.

Methodology

The intern will apply quantitative data analysis techniques, including descriptive statistics, hypothesis testing, and possibly multivariate analysis (e.g., PCA or regression modeling), using software such as R or Python. If qualitative data are included in the 2025 survey (e.g., open-ended responses), thematic analysis may also be performed.

Expected Outcomes

• A comprehensive comparative report detailing the evolution of gender equity indicators between 2022 and 2025;
• Visualizations for dissemination (graphs, dashboards, infographics);
• Recommendations for policy or organizational change within Bordeaux Neurocampus;
• Optional contribution to a scientific communication (poster, article, or internal seminar).

Candidate Profile

We seek a motivated Master 2 student in statistics, mathematics, informatics, psychology, sociology, or a related field, with prior experience or coursework in data analysis and an interest in equity and diversity issues in science.

Contact

Amélie Aussel () or Anna Beyeler ()