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Research Intern

156095
Singapore, Singapore, Singapore
Oct 25, 2018

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Job Description

Description

Xilinx develops highly flexible and adaptive processing platforms that enable rapid innovation across a variety of technologies - from the endpoint to the edge to the cloud. Xilinx is the inventor of the FPGA, hardware programmable SoCs and the ACAP (Adaptive Compute Acceleration Platform), designed to deliver the most dynamic processor technology in the industry and enable the adaptable, intelligent and connected world of the future in a multitude of markets including Data Center (Compute, Storage and Networking); Wireless/5G and Wired Communications; Automotive/ADAS; Emulation & Prototyping; Aerospace & Defense; Industrial Scientific & Medical, and others. Xilinx's core strengths simultaneously address major industry trends including the explosion of data, heterogeneous computing after Moore's Law, and the dawn of artificial intelligence (AI). 


Xilinx Labs, part of the CTO Office at Xilinx, is concerned with innovation, differentiation, and the de-risking of technology.  Goals are to: enable new users; provide a ‘more than Moore’ roadmap; seed new market opportunities; and win the mindshare of startup and research communities. 


Our team of Xilinx Labs Asia-Pacific located in Singapore is growing and we are looking for bold, collaborative and creative people to help us lead the industry transformation to build an adaptable intelligent world. We believe that by embracing diverse ideas, striving for excellence in all that we do, and working together as a unified team, we can accomplish anything. 


The research intern will participate in the projects that span hardware, software, and applications, using a variety of languages, methodologies, and tools.  The technical plan for the is to focus on data center (both communication aspects like software-defined networking, and computation aspects like block chain). It is expected that the research intern will have a background and practical skills that enable contributions within the area. 

Master or Ph.D. student in Computer Engineering, Computer Science, or Electrical Engineering.

 

Project experience includes one or more of: embedded software and systems; FPGA applications and tools; hardware design; machine learning; networking; and security.


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