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Field
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-Performance Computing (HPC) systems are essential infrastructure for solving complex scientific and engineering challenges. However, the rapid growth of HPC alongside AI is creating an urgent sustainability
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temperature. Now, we plan to transform the material system to platform for quantum technology, a coherent 2D spin-photon interface for networks and sensing. To work towards this goal, this 2-year project will
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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About the role Applications are invited for a Postdoctoral Research Associate in Single-molecule Chemistry and Biophysics to work under the supervision of Professor Yujia Qing for a period of up to
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Biology, Biochemistry, or Biophysics. You should be driven, have experience in protein production and good background in structural biology and biophysics. As your project will likely use a combination of
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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). This consortium pulls together expertise from all over the University, including in diagnostics, data science, drug and vaccine design, preclinical testing and clinical testing and brings it to bear on tuberculosis
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-resistant TB (OxCoD4TB). This consortium pulls together expertise from all over the University, including in diagnostics, data science, drug and vaccine design, preclinical testing and clinical testing and
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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity