Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- CNRS
- Nature Careers
- CEA
- Ecole Centrale de Lyon
- Université de Technologie de Belfort-Montbéliard
- French National Research Institute for Sustainable Development
- INSTITUT NATIONAL DES SCIENCES APPLIQUEES
- Inria, the French national research institute for the digital sciences
- Laboratoire d'Astrophysique de Marseille
- Nantes Université
- Observatoire de la Côte d'Azur
- Université Paris-Saclay (UPS)
- Université d'Artois
- 3 more »
- « less
-
Field
-
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 The candidate will work at the
-
Deadline 12 Sep 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Horizon
-
Leveraging the spatio-temporal coherence of distributed fiber optic sensing data with Machine Learning methods on Riemannian manifolds Apply by sending an email directly to the supervisor
-
learning, focusing on identifying abrupt shifts in the properties of data over time. These shifts, commonly referred to as change-points, indicate transitions in the underlying distribution or dynamics of a
-
statistics and machine learning, focused on identifying abrupt shifts in the properties of data over time. These shifts, known as change-points, indicate transitions in the underlying distribution or dynamics
-
. Processing this response provides estimates of the local variations in acoustic pressure along the fiber, over distances ranging from 40km up to 140km with some systems. This technique, called Distributed
-
fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
-
The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
-
We are looking for a candidate with a Master's degree, Engineer's degree or PhD in computer science, junior or senior, to join a team responsible for the packaging, deployment, and testing