PhD Researcher F/M Investigating Low-Precision Arithmetic for Continual Learning Tasks on Edge Devices
il y a 19 heures
PhD Researcher Position
The Inria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD researcher to investigate the performance impact of using low-precision arithmetic in the context of training and deploying continual learning systems on edge devices.
About the Project
The goal of this thesis is to explore the use of low-precision arithmetic for continual learning tasks on edge devices. This involves investigating the performance impact of using low-precision arithmetic in the context of training and deploying continual learning systems.
Key Responsibilities
The successful candidate will be responsible for:
- Implementing, testing, and adapting various low-precision variants of continual learning methods
- Developing and validating task-aware number format precision switching strategies and custom hardware architectures for continual learning tasks
- Designing and implementing a prototype of an accelerator for training in the context of low-precision continual learning
Requirements
To be eligible for this position, the candidate should have a strong background in computer science and hardware design, as well as experience with modern deep learning techniques applied to continual learning tasks. Good programming skills in Python/C++ and an excellent grasp of hardware design languages (e.g. VHDL or Verilog) are also required.
About INRIA
INRIA is a major player in the field of digital sciences, with a strong focus on innovation and research. The Inria Centre in Rennes is a hub for research and development, with a rich ecosystem of research teams, laboratories, and industry partners.
How to Apply
Applications are accepted until the position is filled. The application file should include a CV, motivation letter, transcripts for the courses taken in the last two years of study, contact information and letters of support from two references.
Benefits
- 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
Remuneration
Monthly gross salary amounting to 2100 euros for the first and second years and 2200 euros for the third year
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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...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position F/M Exploring Low-Precision Arithmetic for Continual Learning Tasks on Edge DevicesInria 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 devices. The successful candidate will be part of the TARAN team and...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position F/M Exploring Low-Precision Arithmetic for Continual Learning Tasks on Edge DevicesInria 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 devices. The successful candidate will be part of the TARAN team and...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position in Continual Learning and Low-Precision ArithmeticInria 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...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position F/M Exploring Low-Precision Arithmetic for Continual Learning Tasks on Edge DevicesInria 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...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position F/M Exploring Low-Precision Arithmetic for Continual Learning Tasks on Edge DevicesInria Rennes - Bretagne Atlantique Centre is seeking a highly motivated PhD researcher to investigate the performance impact of using low-precision arithmetic in the context of training and deploying continual learning systems on edge devices.The...
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Rennes, Bretagne, France INRIA Temps pleinJob DescriptionPhD Position F/M Exploring Low-Precision Arithmetic for Continual Learning Tasks on Edge DevicesIn the context of the FAIRe project, we are seeking a highly motivated PhD researcher to investigate the performance impact of using low-precision arithmetic in the context of training and deploying continual learning systems on edge devices.The...
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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...
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Rennes, Bretagne, France INRIA Temps pleinJob Description:We are seeking a highly motivated PhD researcher to join our team at INRIA Rennes - Bretagne Atlantique Centre. As a PhD researcher, you will be working on a project focused on low-precision arithmetic for continual learning tasks on edge devices.Project Overview:While machine learning models have achieved impressive results in recent years...
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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 for edge devices. The successful candidate will be part of the TARAN team and contribute to the development of novel techniques for training and deploying continual learning systems on edge devices.Key...
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