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
-
controlling these molecular networks in vivo . This will be achieved using scRNAseq, spatial transcriptomics, advanced machine learning approaches, and genetic approaches to manipulate the expression of
-
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, 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
-
in the field of medical imaging. The team particularly studies the potential of machine learning methods for an efficient and relevant representation of medical data such as images. The challenges
-
, particularly Python and ML libraries, and use of remote calculation servers. Knowledge of informational, library and archival issues in the digital age and/or mastery of traditional machine learning tools
-
Ifremer - French Research Institute for Exploitation of the Sea | Plouzane, Bretagne | France | about 1 month ago
and biology Good knowledge of machine learning methods (e.g. Bayesian networks or Machine Learning, neural networks) Good modeling and programming skills (e.g. Python, R, Fortran, C++). Proficiency in