Reliable Deep Neural Network Hardware Accelerators PhD Position

Context 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...

Research 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...

Job DescriptionINRIA is seeking a highly motivated PhD researcher to work on a project focused on designing and developing fault-tolerant deep learning architectures for hardware-accelerated artificial intelligence systems.Context and ObjectivesDeep neural networks (DNNs) are widely used in various applications, including image recognition, natural language...

Context and ObjectivesDeep Neural Networks (DNNs) are widely used in machine learning applications, but they are prone to hardware faults that can impact their accuracy and reliability. This PhD position aims to design and develop an optimized algorithm-level fault injection framework to assess the resiliency of DNN hardware accelerators to hardware faults,...

Context and ObjectivesDeep Neural Networks (DNNs) are widely used in machine learning applications, but they are prone to hardware faults that can impact their accuracy and reliability. The goal of this PhD thesis is to design and develop an optimized algorithm-level fault injection framework to assess the resiliency of DNN hardware accelerators to hardware...

Job DescriptionContext and ObjectivesWe are seeking a highly motivated PhD student to join our research team at INRIA. The goal of this PhD project is to design and develop an optimized algorithm-level fault injection framework to assess the resiliency of Deep Neural Network (DNN) hardware accelerators to hardware faults. This framework will enable the...

Context and ObjectivesDeep Neural Networks (DNNs) are widely used predictive models in machine learning, but they require significant energy and resources. To address this, custom Artificial Intelligence (AI) hardware accelerators are being designed to support DNNs. However, these accelerators are prone to hardware faults (HW faults) that can cause...

Context and ObjectivesDeep Neural Networks (DNNs) have become a crucial component in various applications, including object recognition, natural language processing, and robotics. However, DNNs are prone to hardware faults, which can lead to operational failures and detrimental effects on the application. Ensuring the reliability of DNN hardware accelerators...

Context and ObjectivesDeep Neural Networks (DNNs) have become a crucial component in various applications, including object recognition, natural language processing, and robotics. However, DNNs are prone to hardware faults, which can lead to operational failures and detrimental effects on the application. Ensuring the reliability of DNN hardware accelerators...

Context and ObjectivesDeep Neural Networks (DNNs) are widely used predictive models in machine learning, offering excellent results for complex tasks and applications. However, their energy-hungry data movement, computation speed, and memory resources require custom Artificial Intelligence (AI) hardware accelerators. To address data confidentiality issues...

Context and BackgroundDeep Neural Networks (DNNs) are widely used predictive models in machine learning, offering excellent results for complex tasks and applications. However, their energy-hungry data movement, computation speed, and memory resources require custom Artificial Intelligence (AI) hardware accelerators to realize their full potential. The...

Job DescriptionINRIA is seeking a highly motivated PhD researcher to work on a project focused on designing and developing fault-tolerant deep learning architectures for hardware-accelerated artificial intelligence systems.Context and ObjectivesThe goal of this project is to investigate the impact of hardware faults on deep neural networks (DNNs) and to...

Job 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...

Context 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,...

Context 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...

Job DescriptionINRIA 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...

Job DescriptionPhD Position in Unconventional AI Accelerator Reliability EnhancementInria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD student to work on the reliability enhancement of unconventional AI accelerators. The successful candidate will be part of a research team focused on developing innovative solutions for AI...

Job DescriptionINRIA is seeking a highly motivated PhD student to join our team and contribute to the development of reliable and efficient AI accelerators.About the ProjectThe goal of this PhD project is to investigate the reliability of unconventional AI accelerators and propose novel fault mitigation techniques. The project will involve a combination of...

Job DescriptionAt INRIA, we are seeking a highly motivated PhD student to join our team and contribute to the development of reliable AI accelerators.Project OverviewThe goal of this PhD project is to investigate the reliability of unconventional AI accelerators, specifically those based on PIM (Processing-In-Memory) and neuromorphic computing architectures....

Job DescriptionAt INRIA, we are seeking a highly motivated PhD student to join our team and contribute to the development of reliable AI accelerators.Project OverviewThe goal of this PhD project is to investigate the reliability of unconventional AI accelerators, specifically those based on PIM (Processing-In-Memory) and neuromorphic computing architectures....