Status
Scientific disciplines
Research direction
Digital Science and Technology
Affiliate site
Rueil-Malmaison
IFP Energies Nouvelles offers an innovative PhD opportunity at the intersection of Artificial Intelligence (AI) and High-Performance Computing (HPC). This project aims to develop inference engines based on the MLIR (Multi-Level Intermediate Representation) infrastructure to optimize the performance of AI algorithms requiring precise gradient calculations, multi-precision management, and efficient execution on heterogeneous architectures (CPU, GPU, FPGA, ARM, RISC-V, SiPearl).
The PhD candidate will address key challenges such as optimizing non-linear computations with reduced latency, increased precision, and enhanced performance through multi-precision techniques. They will propose mechanisms to manage interoperability between AI models and numerical solvers in demanding industrial environments, such as subsoil modeling.
The candidate will join a multidisciplinary team and contribute to significant technological advancements in the energy industry. This project will fully leverage modern hardware architectures and optimize the compilation pipeline using MLIR.
Keywords: Generative programming, Compilation, Artificial Intelligence, Computer Science, Deep Learning
- Academic supervisor Dr Fabrice RASTELLO, CORSE Team, INRIA Gronoble, ORCID : 0000-0002-6589-9956
- Doctoral School 217 - Ecole Doctorale Mathématiques, Sciences et Technologies de l'Information, Informatique, Université Grenoble Joseph Fourier
- IFPEN supervisor Dr Jean-Marc GRATIEN, ORCID : 0000-0003-4721-0366
- PhD location IFPEN, Rueil-Malmaison, FRANCE
- Duration and start date 3 years, starting in the fourth quarter 2026 (Novembre 2)
- Employer IFPEN
- Academic requirements University Master degree in Computer Science and Information System, Data sciences, Applied Mathematics
- Language requirements English level B2 (CEFR)
To apply, please send your cover letter and CV to the IFPEN supervisor indicated here below.