Research Assistant Positions at Center for Complex Network Intelligence (CCNI) in Tsinghua Laboratory of Brain and Intelligence (THBI)

Tsinghua University

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Research Assistant Positions at Center for Complex Network Intelligence (CCNI) in Tsinghua Laboratory of Brain and Intelligence (THBI)

 

The Position

The position offered is a research assistant at the Center for Complex Network Intelligence (CCNI, https://brain.tsinghua.edu.cn/en/info/1010/1003.htm), in Tsinghua Laboratory of Brain and Intelligence (THBI).

The candidate, in cooperation with the other members of the team at the CCNI, will contribute to research and to develop pioneering algorithms at the interface between information science, physics of complex systems, complex networks and machine intelligence, with a particular focus on brain/life-inspired computing for big data analysis.

The research consists both of theoretical topics, which are exploited to design novel and more efficient artificial intelligence algorithms; as well as applied topics, in which the computational tools that have been designed are applied to different scientific domains, such as neuroscience, computational biomedicine and socio-economic data science.

 

About THBI

Tsinghua Laboratory of Brain and Intelligence (THBI) is a new stand-alone interdisciplinary research institute established by Tsinghua University. The institute aims to answer foundational questions about the nature of intelligence – in mind, brain, and artificial systems – through cutting edge, interdisciplinary research efforts. THBI brings together domestic and international scholars from a broad range of fields in the areas of brain science, artificial intelligence, and cognitive science.

 

Requirements

  • Bachelor degree or master degree in computer science (or equivalent computational sciences)
  • Excellent programming skills (the research is performed in MATLAB/Julia, therefore knowledge of these programming languages is welcome)
  • Good communication skills and fluency in written and spoken English
  • Strong motivation and commitment to the work
  • Machine learning and network science experience is valued

 

Application

Applicants should send a CV to all the following addresses:

The review of applications is ongoing and will continue until positions are filled.

Start Date: could start as soon as possible

 

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