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Doctoral Researcher in Deep Learning and Energy Efficiency
Il y a 2 mois
The goal of this doctoral research project is to push beyond the current state of the art and analyze the impact of customized floating-point precision, where the bit width of the exponent and mantissa can change without adhering to any standard, as well as the hardware implementation targeting energy efficiency.
Research ContextIn the framework of the French research project AdaptING, the Electronic Group of INL will work in collaboration with CEA-List. In this context, we are currently seeking a doctoral researcher (m/f) for a 3-year contract, supervised by Alberto Bosio (INL), Bastien Deveautour (INL), and Andrea Bocco (CEA).
Requirements- Master's degree in computer engineering/science with a solid experience in at least one of the following areas: computer architectures, digital circuit design (VHDL, Verilog system), optimization algorithms.
- Good programming skills (Python, C, and C++).
- Previous experience in the field of deep learning is a plus (e.g., knowledge of main deep learning frameworks such as PyTorch and TensorFlow).
- Excellent written and oral communication skills in English.
- Fluency in French is an asset but not required.
