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; knowledge in numerical methods and simulation, particularly for partial differential equations, and basic knowledge in mathematical modeling with/and PDEs, with a focus on fluid or biomechanics, porous media
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differential equations. • Basic knowledge in mathematical modeling with/and partial differential equations, with a focus on fluid or biomechanics, porous media. • Optional/advantageous: Experience with Lattice
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differential equations, computational fluid dynamics, material science, dynamical systems, numerical analysis, stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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, Python, Julia, or MATLAB Knowledge in numerical methods and simulation, particularly for partial differential equations and finite element methods Basic understanding of mathematical modeling with and/or
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/or their active counterparts. • To perform direct numerical simulations of the continuum partial differential equations of fluid dynamics, solid mechanics, soft matter or active matter
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. The faculty members’ research covers a broad range of areas, including scientific computing, algebra and number theory, differential equations and dynamic systems, statistics and data science, etc. More than
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architectures and training algorithms, uncertainty quantification, high-dimensional stochastic systems and high-dimensional partial differential equation systems. Multiple positions available. About the T-5 Group
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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data
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dynamic processes using differential equations, integrals, probability functions, and applied statistics. Therefore, having experience using more than one of the following languages is crucial: Matlab
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization