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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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, 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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dynamic response to disturbances. EmPowerED is a large project with around 38 partners including different universities, research institutes, municipalities, energy communities, distribution system
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they can be leveraged to create flexibility. Through exploring different strategies for modulating processes, such as adjusting production schedules, varying energy consumption rates, and implementing
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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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theoretical modeling, numerical simulation, and experimental validation. Key objectives can include: Developing theoretical and computational models for friction-induced damping in joints and interfaces
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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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PhD student to establish recipes to provide post-plasma catalysis with different C2Hy distributions and different enthalpy content for optimization of post-plasma catalysis into C2H4. PhD candidate in
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is