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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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. The positions are initially limited to two years. Our research is at the cutting edge of XR technology, and foundations in perception, attention, graphics and vision. As a postdoc, you would contribute to new
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of the following topics will be appreciated, but mostly we look for smart people who enjoy learning new things: Approximate Bayesian inference Differential geometry Numerical computations (ideally with experience in
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scripts, profiling, basic performance optimisation). Experience with CAD tools and CAD automation (e.g. parametric geometry definition and scripting). Compartment and metabolic modelling Experience working
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for plastic discrimination and sorting in an industrial setting. Testing and benchmarking the system with respect to experimental geometry, operational speed, and robustness against noise factors. Advanced data