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: Applications accepted all year round Details Data assimilation combines physical models with experimental or numerical data to produce dynamically consistent flow reconstructions. In turbulence, where full
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
-tolerance to the insulin producing beta cells, and 2) Development of immunotherapies for T1D. The work makes use of several genetically manipulated mouse models of T1D, as well as humanized mouse models, and
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datasets, modelling approaches, and performance metrics; develop physics-informed and data-efficient machine learning models to predict sorbent behaviour from sparse and multi-modal experimental data; and
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complementary data from other Mars missions to strengthen current models and provide comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research. We are looking for a Research Fellow to work on the thermal catalysis for CO2
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Astrophysics, Space Physics, Aerospace Engineering, Applied Physics, or a closely related field. Previous experience with numerical modelling and simulation relevant to space systems of astrophysics and a
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water models for accurate and efficient simulation of free-surface flows. This includes model derivation, model analysis, and development and implementation of numerical methods. For more information, see
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. For the Working Group “Ecosystems in Transition” in RD1 at PIK, we are offering a PhD position (m/f/d) (Position number: 10-2026 PhD ARTECO) in the field of ecological modelling of complex arctic landscapes
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quantum many-body theory with a focus on quantum impurity models (particularly Kondo model). Strong computational skills (with Python or Julia or C++ or Matlab or equivalent) and using numerical techniques
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with Customer Relationship Management (CRM) or talent management systems. Knowledge, Skills, and Abilities (KSAs) Deep knowledge of experiential learning models, e.g., internships, co?ops, clinical