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pulses develop numerical codes to calculate the system dynamics by solving partial differential equations (e.g. Schrödinger equation, von Neumann equation) model the coupling to lattice vibrations (i.e
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Description The majority of hydrological models rely heavily on the principle of mass balance, often represented through Ordinary Differential Equations (ODEs). These models encapsulate
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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global analysis, functional analysis or analysis of partial differential equations Language proficiency in English or German These posts are designed to serve in fostering young researchers. It gives