Haichao Miao

Haichao Miao

Postdoctoral Researcher @ Lawrence Livermore National Laboratory

About Haichao Miao

Haichao Miao is a Postdoctoral Researcher at Lawrence Livermore National Laboratory, where he has worked since 2020. He has a diverse academic background in medical informatics and sinology, with previous research positions at institutions such as Harvard University and the AIT Austrian Institute of Technology.

Work at Lawrence Livermore National Laboratory

Haichao Miao has been employed as a Postdoctoral Researcher at Lawrence Livermore National Laboratory since 2020. In this role, Miao engages in advanced research initiatives, contributing to the laboratory's mission of addressing national security challenges through scientific innovation. The position has allowed Miao to apply expertise in protein-DNA system design and other relevant fields.

Previous Research Experience

Prior to joining Lawrence Livermore National Laboratory, Haichao Miao worked at the AIT Austrian Institute of Technology GmbH as a Postdoctoral Researcher for five months in 2020. Miao's research focused on the design of protein-DNA systems. Additionally, Miao served as a Visiting Researcher at Harvard University for two months in 2018, contributing to various research projects during this time.

Educational Background

Haichao Miao has a strong academic foundation in medical informatics and sinology. Miao studied at Universität Wien, achieving a degree in Sinologie from 2008 to 2010. Miao also attended Technische Universität Wien, where Miao earned a Bachelor of Science (BSc) in Medical Informatics from 2007 to 2013, followed by a Master of Science (M.Sc.) in the same field from 2012 to 2015.

Postdoctoral and Research Roles

Miao's career includes significant roles at Technische Universität Wien, where Miao worked as a Post-doctoral Researcher from 2019 to 2020 and as a Project Assistant in Scientific Visualization from 2015 to 2019. Miao also held a position as a PhD Candidate at AIT Austrian Institute of Technology GmbH, focusing on the visualization and modeling of DNA nanostructures from 2017 to 2020.

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