L'IRSN, Etablissement Public à caractère Industriel et Commercial (EPIC) – dont les missions sont désormais définies par la Loi n° 2015-992 du 17 août 2015 relative à la transition énergétique pour la croissance verte (TECV) – est l'expert public national des risques nucléaires et radiologiques. L'IRSN concourt aux politiques publiques en matière de sûreté nucléaire et de protection de la santé et de l'environnement au regard des rayonnements ionisants. Organisme de recherche et d'expertise, il agit en concertation avec tous les acteurs concernés par ces politiques, tout en veillant à son indépendance de jugement.

The precision and the validity of the neutronic simulations depend directly on the nuclear data used in those simulations. A new nuclear data library, JEFF (Joint Evaluated Fission and Fusion) 4, is planned to be released shortly and an important work of testing and validating this library on experimental data is performed by the scientific community, especially in Europe. The differences between the measured values and those obtained via, for instance, Monte-Carlo simulations (without any physical assumptions) are considered as biases that are only due to nuclear data used in the simulations. Thus, the nuclear data can be adjusted with the target to reduce those biases, resulting in a new nuclear data set with an improved simulation accuracy. The experimental data used in this study includes cross section measurements, critical experiments as well as fuel composition depletion.

The work of this internship follows a collaborative work of researchers from Switzerland, Netherlands and France, within the JEFF community. The student's work will first focus on the usage of Python scripts developed by a Swiss researcher. This script performs the nuclear data adjustment using pre-calculated sensitivity coefficients of the quantities of interest, for instance the keff, to nuclear data. The main goal of the internship is to perform the adjustment of nuclear data varying different assumptions, particularly the experimental data selection.

This study will allow to verify the robustness of the input data used and thus the reliability of the performed adjustment. If the time schedule allows it, the student could present his/her work during a meeting of the JEFF community. A short visit in Switzerland to work closely with Swiss researchers could also be considered during the internship. This internship will allow the student to discover the nuclear data topic by contributing directly to the validation of the new JEFF-4 library, as well as the experiments and the corresponding simulations, available to such a validation.

Through the framework in which this work will be performed the student will discover collaborative research at an international level. This work will give also some knowledge about the numerical methods of adjustment (data assimilation).

Master 2 (University) degree internship or final internship of engineering diploma, if possible with a specialization in nuclear engineering. Python programming language knowledge would be appreciated.

La diversité est une des composantes de la politique RSE, RH et Qualité de Vie au Travail à l’IRSN.

Par conséquent, nous accordons la même considération à toutes les candidatures, sans discrimination, pour inclure tous les talents.

Quelles que soient les différences, nous souhaitons attirer, intégrer et fidéliser nos candidats et nos collaborateurs au sein d’un environnement de travail inclusif.

L'IRSN conduit une politique active depuis de nombreuses années en faveur de l'égalité des chances au travail et l'emploi des personnes handicapées. Si vous êtes en situation de handicap, n'hésitez pas à nous faire part de vos éventuels besoins spécifiques afin que nous puissions les prendre en compte.