Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
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
-
Acoustic Sensing (DAS), is currently experiencing growing interest in an increasing number of applications, e.g., traffic transportation monitoring, structural health monitoring, and natural hazards
-
societal challenges. Embedded in Luxembourg's diverse and multicultural society, the University offers a welcoming, multilingual environment where students and researchers from around the world feel at home
-
societal challenges. Embedded in Luxembourg's diverse and multicultural society, the University offers a welcoming, multilingual environment where students and researchers from around the world feel at home
-
management is a plus. Rigor, motivation, scientific creativity and originality, writing skills, conciseness, sense of priority and ability to work in a team. Languages: fluent command of English, knowledge
-
multinational environment and interact positively with team members and stakeholders Flexibility, adaptability, autonomy, target and detail-oriented Rigor, motivation, conciseness, sense of priority Past
-
societal challenges. Embedded in Luxembourg's diverse and multicultural society, the University offers a welcoming, multilingual environment where students and researchers from around the world feel at home
-
societal challenges. Embedded in Luxembourg's diverse and multicultural society, the University offers a welcoming, multilingual environment where students and researchers from around the world feel at home
-
. SequoIA focuses on urban monitoring using Distributed Acoustic Sensing, a technique that repurposes existing telecom optical fibers as continuous, high-resolution seismo-acoustic sensors. This passive and
-
limitation of all these techniques is that they are all indirect, in the sense that the loss function that is optimised is not the imputation error. The main challenge is that, in practice, we do not have