PhD Position F/M Reliable Deep Neural Network Hardware Accelerators Developer
il y a 3 semaines
Job Context and Requirements
We are seeking a highly motivated PhD researcher to join our team at INRIA and contribute to the development of fault-tolerant deep learning hardware. The successful candidate will have the opportunity to work on a cutting-edge research project that aims to design and develop an optimized algorithm-level fault injection framework for assessing the resilience of deep neural network (DNN) hardware accelerators to hardware faults.
Main Responsibilities
- Design and develop a methodology for large-scale fault analysis on state-of-the-art DNN hardware architectures.
- Develop an optimized accelerated fault injector framework enabling large-scale fault simulations.
- Explore different reliability assessment strategies, including training faulty networks, identifying malignant faults, and evaluating fault tolerance during inference.
Key Skills and Qualifications
- Master's degree in Computer Science, Computer Engineering, or Electrical Engineering.
- Good knowledge of computer architectures and embedded systems.
- HW design: VHDL/Verilog basics, HW synthesis flow.
- Basic programming knowledge (C/C++, Python).
- Basics of Machine Learning (PyTorch/TensorFlow).
- Experience with High-Level Synthesis (HLS) and fault-tolerant architectures is a plus.
Working Conditions
- Subsidized meals.
- Partial reimbursement of public transport costs.
- Possibility of teleworking (90 days per year) and flexible organization of working hours.
- Partial payment of insurance costs.
Salary
Monthly gross salary amounting to 2000 euros for the first and second years and 2100 euros for the third year.
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