AI & education engineer

Level of qualifications required : Graduate degree or equivalent

Fonction : Temporary scientific engineer

Context

Within the framework of a partnership (you can choose between)

The goal is to develop methods to facilitate programming learning and measure their impact on learning outcomes.

The work will be conducted within the SODA team at Inria Saclay.

Assignment

• Develop AI tools for education (LLMs)
• Automatically generate tests
• Analyze large-scale data
• Conduct randomized classroom trials: measure the impact of the developed tools on learning outcomes
• Publish papers at conferences (AIED, EDM, LAK, )

For a better understanding of the proposed research topic: More details and a bibliography are available at the following URL.

Collaborations: The recruited individual will also be involved with the ATLAS Chair: Nicolas Thiéry, Michel Beaudouin‑Lafon (LISN, Orsay), and potentially computer science professors participating in the study; or other international collaborations.

Main activities

• Implementing LLM tools to collect student questions and provide them to teachers in a pseudonymised format
• Automatically generating test cases to test code robustness
• Conducting randomized controlled trials in classrooms
• Contributing to international publications

Additional activities:

• Giving seminars

Skills

Technical skills and required level:

• Data analysis (pandas, matplotlib, scikit‑learn)
• Web
• Possible experience with Jupyter notebooks and LLM

Languages:

• French

Benefits package

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organisation 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

According to qualifications and professional experience

• Theme/Domain : Optimization, machine learning and statistical methods Software Experimental platforms(BAP E)

Defence Security

This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. relating to the protection of national scientific and technical potential (PPST). Authorization to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.

Recruitment Policy

• You are sensitive to the challenges of human learning.
• You possess scientific rigor and a curiosity for innovation.
• You have an affinity for open-source projects with societal impact.
• Experience in competitive programming is a plus.