-
oscillation analyses • Practical Experience of deploying state-of-the-art machine learning techniques Desirable: • Ability to develop and apply new concepts • Verbal and written communication skills • Ability
-
(Machine Learned Potentials) type approaches, and/or multi-objective approaches. - in-depth knowledge of Python programming languages (or C++, Fortran) and the Unix system; - Certified level in written and
-
processing, involving machine learning techniques, as well as active participation in data collection from the detectors deployed on site. - Analysis of particle physics data applied to muography: filtering
-
, reinforcement learning, temporal logic, automata learning, etc. More specifically, we will explore reinforcement learning techniques to develop black-box testing algorithms for timed automata. We will explore
-
will focus on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural
-
Deep Learning-type methods. The focus will be on geodesic methods, the search for paths of minimum length according to an adapted metric, imposing for example a penalization of the curvature. In addition
-
This position will consist of using "deep learning" methods, in particular CNNs and "transformers" for the processing of data from the IASI instrument from CNES. These observations are brightness temperature
-
programming, CAD or generative design tools, knowledge in crystal plasticity, continuum mechanics, additive manufacturing, data science, and machine learning. Additional comments More information about the
-
knowledge of the rules governing microbial assemblages in order to propose practical solutions for improving wetland management and governance. The specific objectives of the MAEWA project are to acquire new
-
experiments and numerical simulations and will be divided into three parts: Microstructure: 1.1. Experimental Characterization: Using X-ray tomography, image analysis with conventional tools or deep learning