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Techniques Laboratory description : Laboratoire Interdisciplinaire Carnot de Bourgogne As part of the LabCom TeleMAQ (Testing the Limits of Quantum Machines and Algorithms) project, established between
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16 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire lorrain de recherche en informatique et ses applications Research Field Computer science Mathematics » Algorithms
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biomedical applications, with a strong emphasis on neurodegenerative diseases. Your role Act as the core developer for software projects within the group, translating cutting-edge deep learning algorithms
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, forecasting, and optimisation within a digital twin environment. Your specific activities will include (but are not limited to): · Developing and implementing algorithms for automated process discovery
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The main goal of this PhD is to develop advanced
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preservingmachine learning. Strong communication and writing skills; ability to work both independently and as part of a team. About the team The DATA team develops foundational mathematical and algorithmic
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
(www.code-saturne.org ), EDF developed recognized expertise in neural-network-based learning for handling simple fluid flows with high accuracy [Meyer et al., 2021]. In 2022, an algorithm hybridizing POD
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 2 months ago
projects DeepGreen and CAMELIA, which are dedicated to developing hardware and software technologies for the acceleration of Artificial Intelligence workloads. Under the DeepGreen project, work focuses on
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pipelines, as well as developing new algorithms and data-processing routines. This relates also to new methods such as wearables, markerless motion capture, machine and deep learning (ML/DL) and artificial
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of operators. The objective of this postdoctoral project is to develop methods and systems for the efficient, reliable, and task-specific execution of workflows involving LLMs, with a primary emphasis on