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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
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via thermodynamic power cycles. However, conventional expansion machines (turbines or volumetric devices) face significant limitations at low power scales: - Turbomachinery suffers from reduced
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qu'avec un.e autre doctorant.e et deux post-doctorant.e.s également recruté.e.s via JET2SB. Le.a doctorant.e fera donc partie d'un effort de recherche particulièrement dynamique. Dans le cadre du projet
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(with openness to learning others): Computational protein design or molecular modeling Protein biochemistry / structural biology Cell biology and receptor signaling Good communication skills in English
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train station or by car (parking available). Public transportation costs are partially covered. The challenge is to establish a novel reconstitution method for spliceosome from human cellular extracts
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will explore if learning and memory paradigms trigger the recruitment of RNAs to specific synaptic compartments. Second, the student will study the cellular machineries involved in local RNA recruitment
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-Performance Computing for Exascale" contributes to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. This program is
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this thesis, the student will interact with researchers from these three teams, as well as with another doctoral student and two post-doctoral fellows also recruited via JET2SB. The doctoral student will
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on the Triolet campus of the University of Montpellier and brings together around 250 people, including researchers, teacher-researchers and IT staff, as well as numerous doctoral and post-doctoral students. Its
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laboratory is organized into four research groups: - MSC Group: Composite Materials and Structures - SUMO Group: Surface, Machining, Materials, and Tools - MS2M Group: Modeling of Mechanical Systems and