30 machine-learning-phd positions in France

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 Position : Planning of distributed renewable energy systems with machine learning

objective will be to develop algorithms for predicting and planning the evolution of local energy systems (microgrids) over a time horizon of several years, using machine learning and numerical optimization

Graph-Based Machine Learning for Enhancing Neuroimaging Data Representation and Analysis [FAMOUS]

advances obtained on Graph Neural Networks, on both convolution [5] and pooling [6] steps. 1.2 METHODOLOGY AND WORK PLAN The proposed PhD research program aims to develop innovative graph machine learning

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

Sufficiency in cloud distributed datacenters

to teach in English or French. Practical details PhD will take place at IRIT, the largest computer science research institute in Toulouse, Our team SEPIA works on resource management on various distributed

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

PHD Candidate (M/F/D) Numerical design of bottom-up fabricated optical Huygens metasurfaces

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

Deep Learning with Generative Models for Anomaly Detection

in computer vision, mainly for image synthesis [7, 8] and medical imaging [9]. The proposed PhD research program aims to investigate these recent advances in generative models with deep learning

Learning host-pathogen surface interactome to design novel therapeutics

expertise in macromolecular interactions and docking, structural biology, and deep learning, together with several PhD and master students. Assignment Background: Streptococcus Pyogenes (Group A Streptococcus

Post-doctoral position (M/F) spatio-temporal data analysis

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