28 molecular-modeling-or-molecular-dynamic-simulation PhD positions at University of Nottingham
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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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integrates dynamic “smart” materials into 3D-printed structures, opens new frontiers in both bioelectronics and solar energy harvesting. Our goal is to create adaptive electrode architectures. These advanced
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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study of ever more realistic model systems. Single atom catalysts, where the catalytic site contains only a single metal atom supported on a heterogenous substrate, offers a tantalising prospect as a
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of deep learning models, especially when new training experiences are corrupted. The framework will be validated in robotic control scenarios during EV battery assembly, under process variations such as
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an assessment of the part quality; this will involve the development of laser beam processing on specific aerospace materials, and a model to understand the fundamental mechanisms of the process to identify
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skills, with a well-rounded academic background. Demonstrated ability to develop precision mechatronics/robotics systems and algorithm Ability to develop kinematic and/or dynamic analysis of mechanical
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability