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                Field
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                emerging models by collaboratively exploring various computation models leveraging physical devices properties. This PhD work will focus on FPGA devices in order to build an accelerated spiking neural 
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                ), Department for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden) the Chair of Adaptive Dynamic Systems offers a position as PhD Student / Research Associate in FPGA Design for AI 
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                Dynamic Systems offers a position as Research Associate / PhD Student in FPGA Design for AI Applications (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 
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                . The work will be part of a European project on the creation of a secure chip for IoT systems and in collaboration with the phd student that work on the project for two years now. The main objective 
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                monitoring will also be integrated into this PhD. Thermal prediction models are currently implemented on a Field Programmable Gate Array (FPGA), while the thermal PI controller (which will be further developed 
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                a suit of fast electronics (FPGA) that will allow the following achievements: 1) To rapidly repeat single-particle experimental dynamical trajectories to gain sufficient counting statistics in order 
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                Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion 
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                Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion) in FPGA design, machine learning or a 
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                Hardware Engineer in the Data Acquisition Hardware Group who will use your skills architecting, constructing and programming data acquisition hardware systems composed of field programmable gate array (FPGA 
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                , electrical engineering, materials science, or a related field at the PhD level with zero to five years of employment experience. Hands-on experience in one or more of the following: Cryogenic detectors (TES