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Dr. Jie Han 1999年毕业于清华大学，2004年获荷兰代尔夫特理工大学博士学位，2004年-2007年在NASA INAC（纳米电子与计算研究所）博士后研究员。已发表170余篇学术论文，曾获得the International Symposium on Nanoscale Architectures（NanoArch 2015）最佳论文奖，ISQED 2018、GLSVLSI 2015和NanoArch 2016最佳论文提名。现任职于阿尔伯塔大学电气及计算机工程学院，同时担任IEEE Transactions on Emerging Topics in Computing (TETC) 、IEEE Transactions on Nanotechnology和Microelectronics Reliability (Elsevier Journal) 期刊副编辑。阿尔伯塔大学的电气和计算机工程系在北美排名第14位，在全球排名第43位。

更多信息请查看Dr. Jie Han个人主页：http://www.ece.ualberta.ca/~jhan8/

招收1-2名2020年9月入学的博士或硕士生，研究课题内容包括：
1.计算机硬件，VLSI, FPGA，近似计算和随机计算。
2.神经网络和其他新颖的machine learning应用设计。
3.计算机硬件的可靠性、容错能力和能源效率研究。
4.纳米电子和生物应用的新型计算模型。
语言要求：只要求托福或雅思(不要求GRE)。

由于申请截止日期临近，如有意向请尽快将简历发至Dr. Jie Han（jhan8@ualberta.ca），欢迎各位同学来信咨询。


Dr. Jie Han's group at the University of Alberta is looking for 1-2 graduate students at the PhD or Master's level, starting in September 2020.

Dr. Jie Han received the B.Sc. degree in electronic engineering from Tsinghua University, in 1999, and the Ph.D. degree from Delft University of Technology, in 2004. He is currently an Associate Professor with the Department of Electrical and Computer Engineering, University of Alberta, one of the best universities in Canada. Dr. Han was a recipient of the Best Paper Award at the International Symposium on Nanoscale Architectures (NanoArch 2015) and Best Paper Nominations at the 25th Great Lakes Symposium on VLSI (GLSVLSI 2015), NanoArch 2016, and the 19th International Symposium on Quality Electronic Design (ISQED 2018). He is currently an Associate Editor of the IEEE Transactions on Emerging Topics in Computing (TETC), the IEEE Transactions on Nanotechnology, and Microelectronics Reliability (Elsevier Journal).The Department of Electrical and Computer Engineering at the University of Alberta is ranked the 14th in North America and the 43rd in the world overall.

More information can be found at: http://www.ece.ualberta.ca/~jhan8/

Dr. Han's group works on a broad range of topics including:
1. Computer hardware, VLSI, FPGA, approximate computing and stochastic
computing.
2. Neural network and other novel designs for machine learning applications.
3. Reliability, fault tolerance, and energy efficiency in the above systems.
4. Novel computational models for nanoelectronic and biological applications.

The University of Alberta only requires TOEFL or IELTS (but not GRE).

Since the application deadline is approaching, please contact Dr. Han as soon as possible if you are interested.