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Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation
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for establishing properties of quantum programs - Reduction methods and metrics for quantum systems - Decision diagrams for efficient analysis and simulation of distributed quantum programs - Statistical model
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for grid support to future power grids and quantify the performance of the developed control. Your work will involve both theoretical analysis and simulation-based validation of the proposed control method
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qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast experiments, mapping
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and qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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consist of a series of questions based on the application materials. Further information We recommend that you save a copy of the job posting, as it will be removed once the application deadline has passed
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is expected to have a profound knowledge on most of the following topics: Robot control Deep Learning Medical imaging Preferably, the candidate has experience with: Robotic simulation tools Medical
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surgical robots across various surgical applications, using techniques such as advanced sensing, AI-based and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date
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PhD scholarship in Corrosion Mechanisms of Power Semiconductor Device and Components - DTU Construct
, gases and applied potential conditions. The project will also include the development of advanced simulation models to characterize and predict moisture transport through gel substrate and interfacial