General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
2024-31240
Description de l'unité
The Laboratory for the Design of Embedded and Autonomous Systems (LSEA), within the CEA, carries out interdisciplinary activities on physical, reliable and trustworthy systems, in collaboration with industrial, governmental or international partners.
Position description
Category
Mathematics, information, scientific, software
Contract
Internship
Job title
AI system validation by fault injection in simulation H/F
Subject
The project aims to evaluate an AI-based system design based on safety-oriented fault-injection simulations through a virtual platform to reinforce AI learning during design.
Contract duration (months)
6
Job description
To address the issue of AI system verification, validation, and certification, existing work define a design solution combining AI algorithms and conventional algorithms. AI algorithms include all complex and/or black box algorithms that need to be certified. The conventional algorithms include functions that monitor and supervise AI code execution. These monitors are derived from safety and requirement analysis. With this particular combination, we hope to benefit from both approaches: a system that can handle complex decision processes through the use of artificial intelligence and that can provide high confidence by leveraging a monitor written in conventional code. Meanwhile, evaluating the robustness of such AI-oriented systems often involves understanding the impact of fine-grain perturbation regarding the computations. The ability to study high-level and fine grain aspects at the same time requires a significant runtime instrumentation capacity.
To evaluate the safety and robustness of such an AI-oriented system with its HW and SW parts, we think of a methodological approach based on preliminary safety assessment results, functional testing on a virtual platform, fault injection, and uncertainty measurement. Concretely, the evaluation framework will be based on:
• Risk assessment providing some kind of envelope of permissible behavior for the AI system without compromising safety and list of faults and failures with their effects on the system
• An embedded system simulator capable of injecting fault at functional and hardware levels
• Online (at runtime from devices) and offline (from testbench dataset) fault injection (HW/SW) technique to stress the system with regard to faulty scenarios
• uncertainty measures with an estimation of their confidence level
• runtime monitoring for the tracking of fault propagation,
and study of their impact at the algorithmic level
The goal of the project is to implement and validate such an approach on a use case.
Methods / Means
Papyrus, Sophia, Simulation platforms
Applicant Profile
You are passionate about science and novel technologies. You are preparing a Bac+4 or Bac+5 diploma in the field of computer science or alike. You have knowledge of AI, programming languages, embedded systems, simulation, safety assessment.
Position location
Site
Saclay
Job location
France, Ile-de-France, Essonne (91)
Location
palaiseau
Candidate criteria
Languages
- English (Fluent)
- French (Fluent)
Prepared diploma
Bac+5 - Diplôme École d'ingénieurs
Recommended training
Informatique
PhD opportunity
Oui
Requester
Position start date
01/07/2024