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of Architecture and the Built Environment), where you will collaborate closely with a parallel PhD project within the Faculty of Aerospace Engineering focused on meshfree numerical methods. Together, you will work
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research revolves around the following key objectives: Finding analytic expressions for families of numerical Hamiltonians that model magnetic topological semimetals. Classifying such Hamiltonians in terms
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, including thermal behavior and ageing and experiments that lead to accelerated ageing. This requires developing understanding of the underlying physics, methods for data-driven modelling and numerical
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numerical modelling and programming is an advantage; demonstrated ability to work both independently and collaboratively in an interdisciplinary and multicultural research environment; good organizational and
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, chemistry, chemical engineering, or materials science; proven skills in chemical and physicochemical analytical tools. Experience with atomic force microscopy is an advantage; experience with numerical
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, which is time-prohibitive and therefore impractical for large parts. This project therefore aims to develop numerical methods that enable the efficient simulation of the LAFP process while accounting
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the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam generation unit, imaging lenses
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three main phases. In the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam
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, preferably with a proven background in, or willingness to learn, physics-based numerical modelling and programming skills, in Python (preferably), R, MATLAB, or a comparable language. Openness to collaborate
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from a wide-range of disciplines in future climate model development, paleo-climate data collection, and applied mathematics. Your qualities The project requires the development of both numerical skills