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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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to comprehensive activities in basic research as well as applied research in the fields of Nanoscience & Microsystems Engineering and Semiconductor Devices and Circuits along with knowledge and experience in VHDL
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to prototype PCB or ASIC designs to improve the reliability and performance of interconnects for in-house and external projects. You will additionally be responsible for the training and supervision
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, or FPGAs control platforms. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in
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, or FPGAs control platforms. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in
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/or FPGAs) E3 Experience in hardware assembly and fabrication, with experience in PCB manufacturing/ assembly, prototyping, and willingness to acquire new skills, e.g. in additive manufacturing and chip
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manipulation of ultracold gases. Examples include basic electronics, development of FPGA devices, development of narrow-linewidth lasers, laser frequency stabilisation and control, image analysis, data
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, such as the ARM Cortex-M microcontroller for medical device applications Fluency in Matlab, Python, Embedded C, VHDL Ability to assess resource requirements and use resources effectively Understanding
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communication skills. · Skills relevant to the trapping and manipulation of ultracold gases. Examples include basic electronics, development of FPGA devices, development of narrow-linewidth lasers, laser
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of biological brains. Spiking neural networks (SNNs) can offer increased processing speed and reduced power consumption, especially when implemented on dedicated hardware (neuromorphic chips or FPGAs). Standard