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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 10 days ago
for the avatarization process, i.e. obtaining a 3D, animatable model from one or several images. This is a very hard problem as shape fidelity, animatability, fast computation time and low number of required input
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with familiarity with foundation models (e.g. vision language models) and the ability to design and prototype innovative, reliable and reproducible solutions for complex 3D scene understanding tasks
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production and run custom computer algorithms for 3D image registration, fluorescent signal detection, cell/clone segmentation, and annotation. You will organize and maintain the rapidly expanding spatial
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flexible work arrangement agreements on a temporary or permanent basis for any reason at any time. Responsibilities: 3D printing and printer management (30%) • Work with investigators to develop, prototype
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-cell imaging and immunolabeling. These images will then be analyzed in 3D using automated methods. - Manipulate the physical constraints to which nuclei are subjected and compare transcriptional dynamics
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into embryonic structures - Molecular biology techniques - Advanced imaging - Single-cell sequencing - Drug treatments and effect analysis Where to apply Website https://pica.cineca.it/ Requirements Additional
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galaxies. VIEWS leverages the capabilities of the James Webb Space Telescope cycle 3 project GO5018 to provide high-resolution imaging and spectroscopy of six selected Brightest Cluster Galaxies. Two
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structuring of novel light-sensitive poly(amino acid) materials - a paradigm shift in delivering biocompatible devices", reference 101129842 of CICECO - Aveiro Institute of Materials, under the following
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position in the area of microelectronics circuit/system design. The School of Electrical, Computer and Energy Engineering (https://ecee.engineering.asu.edu/ ), one of the eight Fulton Schools of Engineering
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this project is to perform advance image analysis on correlative datasets to extract the underlying knowledge. The technical aspect of this project aims to integrate two cutting-edge microscopy platforms