PhD Positions in Trustworthy AI Hardware Architectures

PhD Position in Trustworthy AI Hardware ArchitecturesWe are seeking a highly motivated PhD researcher to join our team at Inria Rennes - Bretagne Atlantique Centre. The successful candidate will work on the development of trustworthy AI hardware architectures, focusing on the impact of hardware faults on AI decisions and algorithms.About the Research...

Job DescriptionWe are seeking a highly motivated PhD student to join our research team at INRIA and work on a project focused on trustworthy AI hardware architectures. The goal of this project is to study the impact of hardware faults on AI decisions and develop low-cost fault tolerance approaches to ensure the correctness of AI hardware.Key...

About the PhD PositionThe Inria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD researcher to work on the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The goal of the Ph.D. thesis is to study the reliability of AI hardware in the presence of faults and to design low-cost fault tolerance...

Job DescriptionContext and BackgroundAs AI applications are increasingly being deployed on edge devices, there is a growing need to ensure the reliability and trustworthiness of AI hardware. This PhD position aims to investigate the impact of hardware faults on AI decisions and develop fault-tolerant AI hardware architectures.Research ObjectivesThe PhD...

Context and BackgroundThe increasing need to distribute Artificial Intelligence (AI) applications from the cloud to edge devices has led to a growing interest in designing custom and embedded AI Hardware architectures (AI-HW). However, AI-HW is not immune to faults, which can impact AI decisions and explainability. This PhD thesis aims to study the impact of...

About the Research OpportunityWe are seeking a highly motivated PhD student to join our research team at Inria Rennes - Bretagne Atlantique Centre. The goal of this PhD thesis is to investigate the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The successful candidate will analyze the possible failure mechanisms...

Context 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...

Context 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...

Context 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...

About the Centre or DepartmentInria Rennes - Bretagne Atlantique Centre is one of Inria's eight centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness...

Context and BackgroundWith the increasing need to distribute Artificial Intelligence (AI) applications from the cloud to edge devices, there is a growing trend to design 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...

Context 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...

PhD Research Project: Trustworthy AI Hardware ArchitecturesWe are looking for a talented PhD student to join our research team at Inria Rennes - Bretagne Atlantique Centre. The PhD research project aims to investigate the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The successful candidate will analyze the possible...

PhD Position in AI Hardware Fault ToleranceWe are seeking a highly motivated PhD student to join our research team at Inria Rennes - Bretagne Atlantique Centre. The goal of this PhD thesis is to investigate the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The successful candidate will analyze the possible failure...

About the PhD Researcher PositionThe Inria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD researcher to work on the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The PhD researcher will be responsible for analyzing the possible failure mechanisms affecting the hardware, deriving the...

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...

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...

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 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...