201 machine-learning-phd "University of Zurich" PhD positions at CNRS

PhD contract: characterization of volcanic processes using continuous seismic data analysis and machine learning (M/F)

: - 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

PhD Thesis (M/F) Transverse Santé : Deep learning approaches for the analysis of NMR spectra applied to schizophrenia

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

PhD (M/F) Analysis of tree physiology in urban environments: modeling and machine learning using optical and radar imagery

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

PhD Position (M/F) - Physical Learning Using Nanocomponents

design, and innovative computer architectures. Our research interests range from the study of fundamental phenomena to the design of new devices with potential for technological applications in information

M/F: PhD student : Statistical learning for the observation and modelling of displacements using aerial images

inference and machine learning techniques. This will involve learning the specificities of the movements of heterogeneous users of an infrastructure, so as to enable a reliable prediction of collisions, and

PhD on the tolerancing of a machine tool with an overconstrained parallel structure (M/F)

of this project is to develop a new Exechon-type parallel robot architecture that can be moved for machining and drilling tasks on large parts in the aerospace and naval sectors. This architecture has to meet both

PhD in Molecular Modeling of Gas Hydrates (M/F)

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

PhD (M/F) Study of behaviours predictive of well-being and school persistence

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

PhD (M/F)

stable energy levels, which can promote learning in the classroom (Florence et al., 2018). However, despite this evidence, many young people engage in risky health behaviours that can lead to long-term

PhD Position in Physics (M/F)

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