Emplois actuels liés à PhD Position F/M Reliable Deep Neural Network Hardware Accelerators: Design and Development of Optimized Algorithm-Level Fault Injection Framework - Rennes, Bretagne - INRIA
-
PhD Position F/M in Reliable Deep Neural Network Hardware Accelerators
il y a 3 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and benefits of the positionThe successful candidate will be part of a research team focused on designing and developing reliable hardware accelerators for deep neural networks. The goal of this PhD project is to investigate the impact of hardware faults on the accuracy of DNNs and to propose novel fault-tolerant architectures.Key...
-
Reliable Deep Neural Network Hardware Accelerators: PhD Position F/M
il y a 2 semaines
Rennes, Bretagne, France INRIA Temps pleinPh.D. Thesis: Reliable Deep Neural Network Hardware AcceleratorsThe aim of this Ph.D. research is to design and develop an optimized algorithm-level fault injection framework to assess the resiliency of DNN HW accelerators to HW faults.The Ph.D. student will design and develop a methodology to perform large-scale fault analysis on state-of-the-art DNN...
-
Rennes, Bretagne, France INRIA Temps pleinJob Context and RequirementsWe 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...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinResearch Position in Fault-Tolerant Deep Neural NetworksAs part of our research team at INRIA, we are seeking a highly motivated PhD student to work on the design and development of fault-tolerant deep neural networks. The goal of this project is to investigate the impact of hardware faults on the reliability of deep neural networks and to develop novel...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and ObjectivesThe goal of this PhD thesis is to design and develop an optimized algorithm-level fault injection framework to assess the resilience of DNN hardware accelerators to hardware faults. This framework will enable the application of low-cost selective fault-tolerance strategies.Main ActivitiesThe PhD student will design and develop a...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and BackgroundDeep Neural Networks (DNNs) are currently one of the most intensively and widely used predictive models in the field of machine learning. DNNs have proven to give very good results for many complex tasks and applications, such as object recognition in images/videos, natural language processing, satellite image recognition, robotics,...
-
PhD Positions in Trustworthy AI Hardware Architectures
il y a 3 semaines
Rennes, Bretagne, France INRIA Temps pleinJob Context:The INRIA research team is seeking a highly motivated PhD student to work on the development of trustworthy AI hardware architectures. The goal of the project is to design and implement AI hardware accelerators that are resilient to hardware faults and ensure the transparency of AI decisions.Key Responsibilities:Analyze the impact of hardware...
-
PhD Position in Trustworthy AI Hardware Architectures
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and Background:As the field of Artificial Intelligence (AI) continues to advance, the need to distribute AI applications from the cloud to edge devices has become increasingly important. This trend aims to address issues related to data privacy, bandwidth limitations, power consumption reduction, and low latency requirements, particularly in...
-
PhD Position in Unconventional AI Accelerator Reliability Enhancement
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinPhD Position in Unconventional AI Accelerator Reliability EnhancementAt INRIA, we are seeking a highly motivated PhD student to join our research team and contribute to the development of novel AI accelerator architectures.About the ProjectThe goal of this PhD project is to investigate the reliability of unconventional AI accelerators, specifically those...
-
PhD Position in Trustworthy AI Hardware Architectures
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and BackgroundAs the demand for Artificial Intelligence (AI) applications grows, there is an increasing need to distribute AI applications from the cloud to edge devices. This trend aims to address issues related to data privacy, bandwidth limitations, power consumption reduction, and low latency requirements, especially for real-time, mission- and...
-
Unconventional AI Accelerator Reliability Enhancement PhD Position
il y a 2 semaines
Rennes, Bretagne, France INRIA Temps pleinAbout INRIA Rennes - Bretagne Atlantique CentreLocated at the heart of a rich R&D and innovation ecosystem, INRIA Rennes - Bretagne Atlantique Centre is one of Inria's eight centres, boasting more than thirty research teams. As a major and recognized player in the field of digital sciences, it is at the forefront of innovation.Mission OverviewOur team is...
-
Rennes, Bretagne, France INRIA Temps pleinJob Description:We are seeking a highly motivated PhD student to join our team at INRIA Rennes - Bretagne Atlantique Centre. The successful candidate will work on the reliability enhancement of unconventional AI accelerators, focusing on the identification of hardware and software vulnerabilities in PIM accelerators for DNNs and proposing fault mitigation...
-
PhD Position in Trustworthy AI Hardware Architectures
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and BackgroundThe increasing need to distribute Artificial Intelligence (AI) applications from the cloud to edge devices has led to a growing trend of designing custom and embedded AI Hardware architectures (AI-HW) to support energy-intensive data movement, speed of computation, and large memory resources that AI requires to achieve its full...
-
Rennes, Bretagne, France INRIA Temps pleinPhD Position F/M Continual Learning and Low-Precision Arithmetic on Edge DevicesAt INRIA, we are seeking a highly motivated PhD researcher to investigate the impact of low-precision arithmetic on continual learning tasks on edge devices. The successful candidate will be part of the TARAN team and contribute to the FAIRe project.Context: The position is...
-
PhD Position in Trustworthy AI Hardware Architectures
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext and BackgroundThe increasing need to distribute Artificial Intelligence (AI) applications from the cloud to edge devices has led to a growing trend of designing custom and embedded AI Hardware architectures (AI-HW) to support energy-intensive data movement, speed of computation, and large memory resources that AI requires to achieve its full...
-
Rennes, Bretagne, France INRIA Temps pleinAbout the RoleWe are seeking a highly motivated and creative PhD student to join our team at INRIA Rennes, within the TARAN team. The successful candidate will be involved in common initiatives with other members of the FAIRe project.Job DescriptionThe position is focused on investigating the performance impact of using low-precision arithmetic in the...
-
PhD Position in Unconventional AI Accelerator Reliability Enhancement
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinJob Description:We are seeking a highly motivated PhD student to join our team at INRIA Rennes - Bretagne Atlantique Centre. The successful candidate will work on the reliability enhancement of unconventional AI accelerators, focusing on PIM-based architectures.Key Responsibilities:Characterize the radiation-induced impact on system reliability for different...
-
PhD Position in Incremental Deep Learning for Embedded Systems
il y a 3 semaines
Rennes, Bretagne, France INRIA Temps pleinResearch OpportunityThe INRIA is seeking a highly motivated and skilled PhD candidate to work on a research project focused on incremental deep learning for embedded systems. The project aims to design and develop resource-efficient algorithms for edge AI, enabling the deployment of AI models on resource-constrained devices. The successful candidate will...
-
Rennes, Bretagne, France INRIA Temps pleinContext: This PhD position is part of the TARAN team at Inria Rennes, involved in the FAIRe project.Mission: The goal of this thesis is to investigate the impact of low-precision arithmetic on the performance of continual learning systems on edge devices.Objectives:Implement and test various low-precision variants of continual learning methods.Develop...
-
Rennes, Bretagne, France INRIA Temps pleinJob Description:The Inria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD researcher to work on a project focused on continual learning and low-precision arithmetic for edge AI applications. The successful candidate will be part of the TARAN team and contribute to the development of novel techniques for training and deploying continual...
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators: Design and Development of Optimized Algorithm-Level Fault Injection Framework
il y a 1 mois
INRIA is seeking a highly motivated PhD student to work on the design and development of an optimized algorithm-level fault injection framework for assessing the resiliency of Deep Neural Network (DNN) hardware accelerators to hardware faults. The goal of this project is to enable the application of low-cost selective fault-tolerance strategies and to design selective fault-tolerance approaches for DNN HW accelerators.
Key Responsibilities:
- Design and develop a methodology to perform large-scale fault analysis on state-of-the-art DNN hardware architectures.
- Develop a fault injection framework to assess the resiliency of DNN HW accelerators to hardware faults.
- Design selective fault-tolerance approaches for DNN HW accelerators using the analysis provided by the fault injection method.
- Measure the reliability improvements obtained with the above-described methodology and perform a design space exploration to obtain different DNN HW accelerator implementations providing different trade-offs between fault tolerance and energy efficiency.
Requirements:
- 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) is a plus.
- Experience in 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.
