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architecture beyond the CMOS-based scheme and suitable energy-efficient hardware for the unconventional scheme is highly desired for future highly-integrated AI hardware on a chip. The French team at IEMN has
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including hardware in the loop, and relevant industrial case studies, assessing its robustness and computational performance. Collaborate with researchers and industrial partners, contribute
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laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW, or Matlab for instrument control/data processing is required, but you do not
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
: The recruited person will be in connection with the hardware engineer recruited in parallel on task T3.3, who designs and fabricates the physical actuated phantom prototype, for the joint integration and
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software
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. Experience with EMT simulation tools, frequency-domain modelling, real-time simulation or hardware-in-the-loop environments is highly valued. Beyond technical excellence, we seek candidates with intellectual
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the Research Council of Finland (RCF) consortium project focusing on the development of low-field MRI hardware, sequences, image reconstruction and applications, in the Quantitative MRI research group
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should hold a PhD in physics, astronomy, or a closely related field by the start date. Candidates with experience in detector hardware, electronics, and simulation are welcome to apply. Theorists and
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
(health insurance, paid leave, restaurant subsidy, etc.). Access to Inria’s computing infrastructure and to the ĀnandaBot project’s dedicated hardware (GPU servers, robot platforms). Integration in a well
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-CT experiments as part of the user program but the methodology has not been optimised. In this project, we will optimise the scanning method, the hardware and the analysis software to make