54 image-processing-and-machine-learning "UCL" Postdoctoral positions at CNRS in France
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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physics and biology. The institute also benefits from state-of-the-art core facilities, particularly in microscopy (Microscopy Rennes Imaging Center, MRic, https://microscopie.univ-rennes1.fr/ ). Rennes is
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) / InP contact layer (200 nm) / Si substrate The objective of the project is to develop a plasma etching process for this multilayer stack, enabling selective etch stopping on the InP contact layer, which
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data storage, enabling the encoding of text, images, videos, and more into nucleotide sequences. While DNA data storage technologies are advancing rapidly, computation on large DNA-encoded databases
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in the framework of the BBEST PEPR. The project aims to valorise syngas derived from biomass via the OX-ZEO process. This relay catalytic process combines a hydrogenating metal oxide to produce
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provided (equipment, IT, etc.): An office equipped with a computer workstation and shared equipment from the Institut Curie research team Key contacts (within and outside the CNRS): Team leader (Scientific
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four main objectives: - Design and fabricate foam-bonded granular materials, by controlling formulation parameters, shaping processes, and binder solidification. - Characterize the microstructure
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activities will consist in: 1. developing steganalysis methods based on incompatibility search (i.e. study the fact that elements of the image are not compatible with natural images). 2. security analysis
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/ constrain their planetary systems , (ii) analyse the spectropolarimetric data with Zeeman-Doppler imaging (ZDI) to reconstruct the evolving stellar magnetic topologies and characterize the underlying dynamo