The recruited engineer will be co-supervised by MdS and Joliot to implement this new approach. To achieve a portable, efficient code that fully exploits GPUs, the core of the code will be developed using the Kokkos library, for which there is strong expertise at MdS and within the CExA [1]project. Subsequently, a Python interface will be established to make the code easily usable by the community of biologists/bioinformaticians/biophysicists, knowing that ultimately GenEx could interest many teams in various fields of application. The initial applications will focus on yeast, whose genome contains 6k genes each with 300 to 3k base pairs. To interpret experimental results, it is necessary to simulate several million experiments for each gene with a model having about ten free parameters (>100Mh with current methods). One of the long-term objectives will be to conduct a similar study on the human genome (20k genes with 300 to 3M base pairs) on the Exascale machine soon to arrive at CEA. PTC funding is essential to initiate the implementation of the code, and the significant results thus obtained will have a substantial leveraging effect for further development. Mission As part of the GenEx team you will be responsible to develop and test the new software in collaboration with experts of genomics at Joliot and of computer science at MdS. Your mission will include: Discussions and set-up of the physical models to modelise DNA repairs Test of various algorithms to solve these models Development of an highly efficient code, based on Kokkos, to implement the previous