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manual gestures). The SyncoGest project (2025–2030) is an interdisciplinary project conducted jointly by computer scientists (Loria – University of Lorraine / Inria / CNRS), linguists (Praxiling – Paul
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cover will be constrained using Raman spectroscopy of carbonaceous material (RSCM method), complemented by bottom-hole temperatures (BHT) and heat flow data to define present-day thermal gradients
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-depth expertise in Computer Vision and Photogrammetry. - Mastery of state-of-the-art Neural Rendering (NeRF, NeuS, SDF). - Knowledge of Photometric Stereo methods. Operational Skills: - Advanced
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on extending methods for detecting the pose of an object (possibly occluded, even if only partially) held by a person to 360-degree robot vision, in line with mesh detection and biomechanical variables
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ancestral recombination graphs to study of the genetic basis of diseases, incorporating ancient genomes • Apply and develop methods for partitioning heritability and estimating genetic correlations • Develop
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engineering; Formal methods, models, and languages; Interactive and cognitive systems; Distributed systems, parallel computing, and networks. The successful candidate will work closely with teams specializing
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quantification of microplastics in stormwater and urban sediments. - Integrate the results into the development of a method for estimating microplastic loads discharged to rivers at the territorial scale
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quite new within the field of computer vision. The neuromorphic design allows for a much higher acquisition frequency but most and foremost much longer acquisition time spans. This makes it ideal