Postdoctoral Research Scientist: Bayesian Optimal Sensor Placement Using Model Gradients
il y a 2 semaines
Job Context and Requirements
The PhD project will be hosted at the Université Grenoble Alpes in the Inria-AIRSEA team. This project is funded by Numpex, the French exascale supercomputing program.
Project Overview
Bayesian optimal sensor placement is crucial in various applications, especially where data acquisition is expensive. The main challenge lies in determining the optimal locations to observe the system to best infer a specific parameter of interest. While linear models and Gaussian priors are well-understood, the problem becomes more complex when dealing with nonlinear and non-Gaussian systems. A gradient-based approach has been proposed to alleviate this computational burden. This project aims to address various numerical aspects associated with the gradient-based solution for the Bayesian optimal sensor placement problem.
Project Objectives
- Enhance our understanding of the majorize-then-minimize approach used in the gradient-based solution by comparing solutions obtained from the bound-based approach with those from the conventional EIG-based approach.
- Employ randomized linear algebra methods to accelerate the computation of the bound, improving the computational efficiency of the gradient-based approach.
- Incorporate physical constraints into the sensor placement problem, investigating how to take into account constraints on the way the system can be observed to obtain more realistic and practical sensor placement solutions.
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 (90 days/year) and flexible organization of working hours
- Access to vocational training
- Social security coverage
Salary
1st and 2nd year: 2100 euros gross salary/month
3rd year: 2190 euros gross salary/month
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Montbonnot-Saint-Martin, Auvergne-Rhône-Alpes, France INRIA Temps pleinJob OpportunityThe Inria-AIRSEA team at the Université Grenoble Alpes is seeking a PhD candidate to work on a project funded by Numpex, the French exascale supercomputing program. The project focuses on Bayesian optimal sensor placement using model gradients, a majorize-then-optimize strategy.Project OverviewThe PhD thesis will address various numerical...
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Montbonnot-Saint-Martin, Auvergne-Rhône-Alpes, France INRIA Temps pleinResearch Opportunity in Bayesian Optimal Sensor PlacementThe Inria-AIRSEA team at the Université Grenoble Alpes is seeking a PhD candidate to work on a project funded by Numpex, the French exascale supercomputing program. The project focuses on Bayesian optimal sensor placement, a critical task in various applications where data acquisition is...
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