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) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled
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(e.g., Kalman Filter) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness
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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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spectroscopy (important). Experience with building UHV systems. Experience or a desire to learn about quantum device fabrication. Experience in modeling with 3D CAD like autodesk inventor. A strong grasp of
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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Job Description The Institute of Mechanical and Electrical Engineering at SDU invites applications for a PhD position in Neuromorphic Brain-Computer Interface Design. Are you a multidisciplinary
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre