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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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signal processing and closed-loop control algorithms Contract terms The Doctoral student positions are fully funded from start. The position is a fixed-term appointment of four years, with the possibility
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reconstruction algorithms to relax the need for highly uniform magnetic field to conduct MRI scanning, and by doing so, to enable next generation MRI scanners to be far less expensive, ultracompact, and
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knowledge of collaborative software tools, and experience with the implementation of data acquisition or analysis algorithms You have a good track record of published articles in peer reviewed journals
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(Anthropic, OpenAI). Experience with graph algorithms or NetworkX. Familiarity with adaptive learning or educational technology. Experience with WebAssembly technologies (Pyodide, WebR). OAuth2 authentication
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conditions. Work Plan Description Objectives: The main objective of this research project is to use real 2D data to optimize the workflow of FWI inversion algorithms. Methodology: 2D seismic data will be used
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and data-driven frameworks for battery management systems, including health monitoring, early fault detection, and safety-oriented control algorithms. Investigate thermal management, fire suppression
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. The PhD candidate will join the team Methods and Algorithms for Bioinformatics (MAB). - Supervision: - Dr Eric Rivals, HdR, (LIRMM), CNRS Research Director in computer science and bioinformatics (web https
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and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product. The post-doc project is about extending the biomass algorithm to also include data