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time standing on hard and/or uneven surfaces. Lifting, climbing ladders, squatting, twisting, using sprayers, walking on a variety of surfaces, digging, planting and exposure to the elements
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experience · Be a proficient programmer, including in Python, with good coding habits; experience in NEURON, COMSOL, other finite element modeling software, and / or git would be an asset; experience
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astrophysics, and uses a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics doctoral
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demonstrated ability to communicate and interact with a diverse range of stakeholders and students. Demonstrated knowledge in Quasi-Monte Carlo methods and/or finite element analysis and/or machine learning is
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current, relevant industry experience. Proficient communication and computer skills are a must. The ideal candidate will possess some or all of the following skill sets: Basic Finite Element Analysis
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of the project team. Key Skills & Experiences This project will require previous expertise in computational mechanics (preferably finite element methods - with analysis being undertaken in open-source code MoFEM
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modelling using Finite Element (FE) method and FE simulation software (e.g. ANSYS), (3) Model Order Reduction (MOR) methods for mechanical simulation (4) numerical algorithms and models, and scientific
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) computational mechanics, (2) thermo-mechanical modelling using Finite Element (FE) method and FE simulation software (e.g. ANSYS), (3) Model Order Reduction (MOR) methods for mechanical simulation (4) numerical
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-cycle fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Are you motivated to take a step towards a doctorate and open
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or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along the composition-process-structure-property