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PhD Internship - System Infrastructure - Edinburgh

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Oct 16

🚀 Off-cycle Internship


AI generated summary

  • The candidate must be a PhD student/candidate in Computing Science or related discipline with good academic background, programming skills, and evidence of research activity. They should be able to work a minimum of 20 hours per week, preferably full time.
  • The PhD Intern in System Infrastructure at Huawei in Edinburgh will be responsible for applying machine learning in operating systems and distributed systems, utilizing cloud-native technologies like containers and serverless, programming in languages such as C/C++, Go, and Python, and contributing to academic publications in computer science conferences/journals.

Off-cycle Internship

Research & DevelopmentEdinburgh


  • The Systems Infrastructure Research (SIR) lab is part of Huawei, Edinburgh and works on next-generation data centre technologies for the benefit of both internal and external (e.g., cloud) users. Our current areas of interest are serverless systems, cluster scheduling, operating systems, heterogenous hardware (CPU/GPU/NPU) and machine learning applied to systems software.
  • Huawei is looking for PhD interns in computer-related majors. If you are interested in operating systems, distributed systems, cloud-native applications, machine learning and have some project experience or academic research achievements, we’d love to hear from you.


  • PhD Student/Candidate in Computing Science or related disciplines;
  • Good academic background and programming skills, publications in conferences or journals in the related fields (or other evidence of research activity);
  • Able to work minimum 20 hours per week, full time is preferred;

Education requirements


Area of Responsibilities

Research & Development


  • Strong background in operating systems and/or distributed systems.
  • Strong background in applied machine learning.
  • Experience with cloud-native technologies such as containers, Kubernetes, serverless etc.
  • Good programming skills, master of at least one language, such as C/C++, Go, Python etc.
  • Good communication, presentation and teamworking skills.
  • Publications in peer-reviewed computer science academic conferences/journals


Work type

Full time

Work mode