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microcontrollers (e.g., Arduino). Analysis and processing of biological signals Development of algorithms in Python for real-time signal processing. Extraction and analysis of multi-signal cross-frequency coupling
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influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
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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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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 13 days ago
developed an in situ data processing approach, called Deisa, relying on Dask, a Python environment for distributed tasks. Dask defines tasks that are executed asynchronously on workers once their input data
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 29 days ago
) algorithms for the identification of unknown BRP model parameters from time-course, single-cell (growth and gene expression) measurements over cell lineages. Develop methods for estimation of unobserved
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Institut of Mathematics of Marseille | Marseille, Provence Alpes Cote d Azur | France | about 2 months ago
nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential
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strong background in scientific computing to contribute to various algorithmic patterns in an agile development environment. Within an Agile team set up: - You will contribute according to your expertise
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for: • Contributing to various tasks related to the modeling of lipids and membrane proteins involved in lipid droplet biogenesis. • Developing and implementing the POP-MD algorithm in the OpenMM software
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analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of nonstationary models and algorithms for analyzing various
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 2 months ago
multidisciplinary team involving image processing labs (e.g., CMAP) and French hospitals (e.g., CHU Kremlin-Bicêtre, Hôpital Foch, Institut Mutualiste Montsouris, Institut Gustave Roussy). Phase 1: Design and develop