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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 6 hours ago
absorption. Developing fast spectral radiance simulation techniques and implementing the observational system simulation experiment (OSSE) based on GISS climate model, which will be applied to research
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Bioprocess Modeling (Conceptual process simulations) is a major requirement for this position. Familiarity with both GUI-based process simulation tools (e.g., Aspen Plus, SuperPro Designer), and Open-Source
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Your Job: In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will
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and Informatics (Numerical Analysis; simulation, optimisation and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering), Condensed Matter Physics
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attention to phenomena dependent on strain rate, temperature, thermal history, and microstructure; elasto-viscoplastic and micromechanical constitutive modeling, developed in academic and/or industrial
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-fidelity management within a multi-objective constrained closed system design optimisation can allow a highly complex system and environment to be more accurately modelled and simulated, accounting
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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and data-based models for describing complex materials and (re)active molecules with a focus on their interfaces. Development and implementation of new methodologies and algorithms for simulating
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production