PhD Student in Advanced Sensor Placement Techniques

Il y a 2 mois


MontbonnotSaintMartin, Auvergne-Rhône-Alpes, France INRIA Temps plein

Job Context and Benefits

The PhD thesis will take place at the Université Grenoble Alpes in the Inria-AIRSEA research team. This project is funded by the French exascale supercomputing program.

Research Mission

Bayesian optimal sensor placement is a critical task in various applications, particularly in scenarios where data acquisition is expensive. The primary challenge lies in determining the optimal locations where to observe the system to best infer a specific parameter of interest.

Research Objectives

  • Enhance our understanding of the majorize-then-minimize approach used in the gradient-based solution by comparing the solutions obtained from the bound-based approach with those obtained from the conventional EIG-based approach.
  • Employ randomized linear algebra methods to accelerate the computation of the bound, which can be expensive to compute in high-dimensional settings.
  • Address the challenge of incorporating physical constraints into the sensor placement problem, including technical, financial, and physical constraints.

Advantages

  • 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 (90 days/year) and flexible organization of working hours
  • Access to vocational training
  • Social security coverage

Remuneration

1st and 2nd year: 2100 euros gross salary/month

3rd year: 2190 euros gross salary/month



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