Sort by
Refine Your Search
-
develop techniques to tackle the dynamics of these systems both in imaginary and real time. The latter will form a quantum inspired quantum computer emulator that should be able to tackle large systems
-
Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 24 days ago
: Good programming skills, preferably in Python, and strong analytical abilities. A solid background in machine learning, computer security, privacy, distributed systems, or a closely related area
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
into resources that can be used for machine learning. The PhD will therefore investigate multimodal approaches that connect visual sign-language information with textual representations under low-resource
-
Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
applications will be tackled. The first concerns electrical machines like power plant alternators for which EDF has developped numerical simulators and has large sets of sensor data (measuring leaking flux
-
archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
-
Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
to significantly accelerate computations while maintaining sufficient physical accuracy for geoscience applications. Inspired by methods from computer graphics, this approach could enable unprecedented resolutions
-
are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
-
modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
-
of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
-
) and/or machine learning (about 10 PIs). The Physics Laboratory is about 180-member strong and conducts world-leading research on a broad range of topics, including quantum technology, statistical