Sort by
Refine Your Search
-
: - Apply unsupervised machine learning concepts to the analysis of continuous seismograms recorded in the vicinity of active volcanoes, in order to extract information about the state of the volcano and the
-
experimental campaigns to acquire the data required for his thesis, as well as for the MONI-TREE project as a whole. The PhD will take place in LETG-Rennes, with expected missions to ONERA's Palaiseau for works
-
specialized in Technology-Enhanced Learning (TEL) and Human-Computer Interaction (HCI). In particular, SICAL has extensive experience in behavior analysis using multimodal data in different contexts, including
-
of this PhD research is to develop novel optimization strategies for laser-plasma accelerators through the application of machine learning algorithms. Laser-plasma accelerators offer tremendous promise for
-
is an impossible task in metasurfaces composed of millions of elements. The PhD aims to develop methods using machine learning surrogate models to solve this complex design problem. The project aims
-
machine learning have transformed our approach to inverse problems in various fields, notably in medical imaging, enabling a deeper understanding of complex data structures. However, although sophisticated
-
machine learning, speech science, cognition and behavioural studies. If all disciplines are addressed in this PhD position, candidates without expertise in some of the areas listed below are nevertheless
-
friendly refrigeration [1]. To do so, this PhD aims to develop original modeling methods, based on the development of Machine Learning tools, allowing for the description of complex molecular systems
-
laboratory of Sorbonne Université and CNRS. The PhD applicants will be hosted by the “Machine Learning and Deep Learning for Information Access” team (MLIA - https://www.isir.upmc.fr/equipes/mlia/ ), which
-
of Research ExperienceNone Additional Information Additional comments Programming skills in Python/C++ are expected, as well as an interest in research, machine learning, bio-inspiration, electronics, and