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process techniques for the development of ion channel simulation schemes. Design, program and maintain the code necessary for these simulation models. Run numerical simulations. Provide support for
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linear algebra, numerical methods for PDEs and dynamical systems, stochastic methods in statistical mechanics, hydrodynamic limits, interacting many-body systems, quantum macroscopic evolution equations
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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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: Applications accepted all year round Details Data assimilation combines physical models with experimental or numerical data to produce dynamically consistent flow reconstructions. In turbulence, where full
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mechanisms using computer simulations and the methods of non-equilibrium statistical physics. The Research The PhD student will work under the supervision of Dr. Philip Bittihn within the European Doctoral
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measurement techniques). Desirable additional qualifications include knowledge in additive manufacturing (3D printing) and experience with numerical simulation methods (e.g., finite element methods, FE
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on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the objectives to achieve: The workplan proposed comprises two topics, each to be tackled by each studentship offered: Topic 1 - Automatic
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, Process Engineering, Computational Science, or a related discipline Strong foundation in fluid mechanics, gas–liquid two-phase flows, numerical methods (FVM, FEM), and two-phase flow instrumentation
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methods for quantitative characterisation and forecasting of deep fluid circulation" (task leader: R. Chassagne) within the "PEPR sous-sol bien commun PC9", and will therefore use data from the Rhine Graben
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-Documented ability to teach a range of core and advanced courses in mathematics (e.g., calculus sequence, linear algebra, differential equations, probability and statistics, numerical methods, optimization