Emplois actuels liés à PhD Researcher: Reliable Deep Neural Network Hardware - Rennes, Bretagne - INRIA
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 2 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...
-
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...
-
Rennes, Bretagne, France INRIA Temps pleinJob 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...
-
Reliable Deep Neural Network Hardware Accelerators PhD Position
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinJob DescriptionResearch ContextINRIA is seeking a highly motivated PhD student to work on a research project focused on designing and developing optimized algorithms for fault-tolerant deep neural network hardware accelerators. The goal of this project is to improve the reliability of AI hardware platforms, particularly in safety-critical applications such...
-
Rennes, Bretagne, France INRIA Temps pleinContext 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,...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinJob 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...
-
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 pleinContext 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...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 4 semaines
Rennes, Bretagne, France INRIA Temps pleinContext 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...
-
Rennes, Bretagne, France INRIA Temps pleinContext 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...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 3 semaines
Rennes, Bretagne, France INRIA Temps pleinContext 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...
-
Rennes, Bretagne, France INRIA Temps pleinContext 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...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 3 semaines
Rennes, Bretagne, France INRIA Temps pleinContext 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...
-
PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
il y a 1 semaine
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,...
-
Reliable AI Hardware Architectures PhD Researcher
il y a 2 semaines
Rennes, Bretagne, France Inria Temps pleinPhD 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 F/M Reliable Deep Neural Network Hardware Accelerators
il y a 2 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...
-
Rennes, Bretagne, France INRIA Temps pleinJob 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...
-
Reliable AI Hardware Architectures PhD Researcher
il y a 2 semaines
Rennes, Bretagne, France Inria Temps pleinAbout the Research ProjectThe Inria Rennes - Bretagne Atlantique Centre is conducting research on the impact of hardware faults on AI decisions and algorithms developed to explain AI models.The goal of the research project is to study the reliability of AI hardware in the presence of faults and to design low-cost fault tolerance approaches to efficiently...
-
PhD Position in Trustworthy AI Hardware Architectures
il y a 3 semaines
Rennes, Bretagne, France Inria Temps pleinPhD 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...
-
PhD Researcher in Fault-Tolerant AI Hardware
il y a 2 semaines
Rennes, Bretagne, France Inria Temps pleinAbout 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...
PhD Researcher: Reliable Deep Neural Network Hardware
Il y a 2 mois
INRIA is seeking a highly motivated PhD candidate to contribute to cutting-edge research in the field of reliable deep neural network hardware accelerators.
Deep learning models are revolutionizing various industries, from healthcare and robotics to finance and entertainment. However, the increasing complexity and deployment of these models on edge devices demand robust and reliable hardware solutions.
This research position focuses on developing fault-tolerant strategies for deep neural network hardware accelerators, aiming to enhance both reliability and energy efficiency. The successful candidate will work within a team of experts to explore innovative techniques for mitigating the impact of faults in AI hardware.
Research Objectives:- Conduct comprehensive fault analysis on deep learning hardware architectures to identify vulnerabilities that affect classification accuracy.
- Develop strategies to simplify fault injection processes and create an optimized framework for reliability assessments.
- Design novel error correction mechanisms to improve the fault tolerance of deep neural network accelerators.
- Strong foundation in computer architecture and embedded systems.
- Experience in hardware design and basic programming concepts.
- Familiarity with machine learning tools and algorithms.
- High-level synthesis experience is a significant advantage.
- Knowledge of fault-tolerant architectures is highly desirable.
Candidates should hold a Master's degree in computer science, electrical engineering, or a related field. Excellent communication skills and the ability to work effectively in a team environment are essential.
