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in the group optical medical devices. The works is aiming to develop optical devices and processing algorithms to guide surgeons during cancer surgery using fluorescence measurements. The post is based
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variational models and deep learning techniques. You will implement and validate reconstruction algorithms, ensuring their performance, robustness, and efficiency for clinical application. You will participate
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop
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-luminosity phase of the LHC. The successful candidate will work in close collaboration with other members of the Particle Physics team, and with members of the Computing, Algorithms and Data team at L2IT
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8 Oct 2025 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Mathematics Mathematics » Algorithms Mathematics » Applied mathematics Researcher
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opportunity to choose between two missions: • Mission 1: Improve new automated algorithmic schemes to quickly, efficiently and robustly detect and extract recorded geophysical signals related to earthquakes
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algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran
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Eligibility criteria . PhD in atmospheric sciences • Knowledge of cloud physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work
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recognitions and multi-class neural network algorithms. We propose to apply this emerging method to study samples from Europe, South Africa, and East Asia dated between 1.8 Ma and 60 thousand years ago (ka
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 24 days ago
variety of mathematical tools and algorithmic approaches (Continuous-Time Markov chains, Mixed-Effects modelling, Branching processes, stochastic simulation) as well as single-cell gene expression datasets