PhD Position in Probabilistic Embedded Systems for Efficient AI Execution

il y a 2 jours


Paris, Île-de-France INRIA Temps plein
Job Description

Context and Benefits

The PhD thesis is funded by the Paris region program and hosted by the Kopernic team in Paris. The position offers a unique opportunity to work on a cutting-edge project in the field of real-time systems and artificial intelligence.

Research Objectives

The PhD thesis aims to propose efficient scheduling algorithms for probabilistic embedded systems on hybrid architectures. The research will focus on developing novel methods for estimating the worst-case execution time and worst-case response time of real-time critical systems.

Main Activities

  • State of the art on probabilistic and statistical approaches for hybrid architectures.
  • Proposal of multicore scheduling algorithms for Directed Acyclic Graph tasks on hybrid architectures.
  • Validation of the results on a case study proposed by StatInf and open-source benchmarks.

Requirements

Technical skills: background on real-time systems is an advantage, but not necessary, while background on embedded systems is mandatory. Python is the main programming language, but being familiar with C/C++ code is expected.

Languages: English and French.

Benefits

  • Subsidized meals.
  • Partial reimbursement of public transport costs.
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave.
  • Possibility of teleworking and flexible organization of working hours.
  • Professional equipment available.
  • Social, cultural, and sports events and activities.
  • Access to vocational training.
  • Social security coverage.


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