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Field
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Completion or near completion of a PhD in Engineering (mechanical, aerospace, civil, petroleum) or Science (applied physics, applied mathematics) with a strong background in CFD and the finite element method
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finite element analysis, finite difference schemes, or Monte Carlo simulations. Mentoring Assist in mentoring graduate and undergraduate students in related projects. Collaborate with faculty and students
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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 program
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distribution in wire based additive manufacturing • Calibration and validation experiments for modelling • Temperature monitoring techniques • Finite element analysis method • Reviewing literature, planning and
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, engineering, materials science, maths, or computer science), or equivalent experience Experience with uncertainty quantification or error analysis Familiarity with numerical methods (e.g., Monte Carlo, Finite
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experience with HHG sources are a plus but not critical. Knowledge of programing languages such as Python (and with finite element simulations specifically) would be also valuable.
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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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codes, finite element or finite different methods, peridynamics, phase field models, multi-objective optimisation methods, CAD. Demonstrated ability to adapt to fast-changing project direction and learn
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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 program
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of new EEG and MEG neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be