Contrat doctoral : RECONSTRUCTION SANS GRILLE DE COURBES DANS LES TRANSFORMEES TEMPS-FREQUENCE

Organisation/Company Université de Haute-Alsace Department IRIMAS Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 20 Apr 2026 - 17:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Off-the-grid sparsity methods are optimization techniques in continuous measurement spaces that have undergone significant fundamental and algorithmic developments over the past 15 years. In particular, they make it possible to explicitly formulate recovery conditions in inverse problems with sparsity constraints and to design algorithms that leverage these conditions (1).

This PhD topic investigates this framework in the context of observing multicomponent signals using time–frequency (TF) transforms. These families of methods provide richer representations of temporal signals, but they also suffer from intrinsic limitations, including time–frequency localization uncertainty and an increase in representation dimensionality. The objective is therefore to detect, identify, and separate the different components of a signal from its TF representation.

This work is part of the broader framework of off-the-grid curve sparsity (2), with TF transforms as the primary representation (extending in particular the work in (3) and (4)). The aim is to develop a comprehensive methodology, including mathematical methods, algorithms, and applications to real data. For the latter, we plan to work on the classification of lung sounds already collected as part of a collaboration with medical practitioners.

Where to apply

E-mail

Requirements

Research Field Computer science Education Level Master Degree or equivalent

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