AI&education engineer, Palaiseau

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, L@S)

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. 2011-1425 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.

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