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will work on the construction of statistical physics models applied to biological systems. They will test them on biological data from several systems in collaboration with our experimental colleagues
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or Statistics or Business Intelligence, or Artificial Learning and Intelligence, or Signal Processing. o Skills in software development and databases. o Good general scientific background, particularly in
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insights into the statistics of seismicity. It is also likely to have an impact on current seismic hazard practices. Supervision The supervisory team will be made up of S. Durand (LGL-TPE, Chargée de
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corresponds to this strategy and to the development of new tools and concepts in statistical physics, enabling to ameliorate the understanding and numerical simulation of physical systems and also to better
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neurodegenerative diseases such as Alzheimer's disease using multimodal data from large databases. Statistical learning methods applied to the data will help identify multimodal phenotypes of the considered
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, embedded systems, statistics, or AI; or hold an engineering degree in one of these areas. Below is the expected profile: 1. Scientific curiosity is paramount. 2. An ability to criticize, advance, and
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to follow the corresponding chemical reaction, 2) rheology to follow the change in mechanical properties (elastic modulus and yield stress) and 3) video imaging to characterize the foam structure (statistics
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3 Apr 2024 Job Information Organisation/Company CNRS Department Center for Theoretical Physics Research Field Physics » Biophysics Physics » Statistical physics Mathematics » Applied mathematics
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of Mathematics (DEMA), Probability and Statistics (EPS), and Geometry, Topology, and Algebra (GTA). Discrete polytopal complexes are recent numerical methods, whose purpose is to design approximations of partial
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physics or computer science, with a solid background in AI/machine learning techniques. A background in plasma transport phenomena as well as an experience with data analysis, statistical methods, and