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of the mechanisms behind model improvements, and paleoclimate simulations and climate projections. Should be familiar with CESM, WRF, SPEAR, CM1, and theoretical atmospheric models, as well as the land modules within
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FCT. solid experience in computational modeling, with relevant skills for the development of models and projects involving photovoltaic systems. Workplan and the objectives to achieve: The main
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to candidates with knowledge of fluid mechanics and (ideally) computational fluid dynamics; experience in MATLAB or equivalent software will be considered an asset Academic degrees obtained in foreign countries
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Science, Mechatronics, Robotics, Mechanical Engineering, or a related field. At least 1 year of relevant technical hands-on experience in a similar role or specific technical scope. Solid knowledge and
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
on identifying biomechanical tipping points at which invasion becomes mechanically unfeasible. The work of the PhD fellow will be theoretical and computational in nature and include: Developing physics-based
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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method thus enables, for a given granular packing, independent control of the mechanical behaviour of the binder and of the amount of binder deposited, both as solid bridges at intergranular contacts and
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
and computational in nature and include: Developing physics-based, deformable cell models of glioblastoma invasion that incorporate nuclear and cytoskeletal mechanics Applying active-matter theory
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at the University of Texas at Austin invites applications for a postdoctoral researcher to study Earth hazards under the Project SHIELD initiative (Science for Hazards, Impact, Evaluation, and Long-term Defense). The
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statistical physics, solid mechanics, or fluid mechanics Experience with data-driven modeling, parameter estimation, or model calibration Familiarity with high-performance computing or large-scale simulations