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Faculty positions in School of Information Science and Technology
Faculty positions in School of Information Science and Technology(SIST), ShanghaiTech University
ShanghaiTech University invites highly qualified candidates to fill multiple tenure-track/tenured faculty positions as its core founding team in the School of Information Science and Technology (SIST). We seek candidates with exceptional academic records or demonstrated strong potentials in all cutting-edge research areas of information science and technology. They must be fluent in English. English-based overseas academic training or background is highly desired.
ShanghaiTech is founded as a world-class research university for training future generations of scientists, entrepreneurs, and technical leaders. Boasting a new modern campus in Zhangjiang Hightech Park of cosmopolitan Shanghai, ShanghaiTech shall trail-blaze a new education system in China. Besides establishing and maintaining a world-class research profile, faculty candidates are also expected to contribute substantially to both graduate and undergraduate educations.
Candidates in all areas of information science and technology shall be considered. Our recruitment focus includes, but is not limited to: computer architecture, software engineering, database, computer security, VLSI, solid state and nano electronics, RF electronics, information and signal processing, networking, security, computational foundations, big data analytics, data mining, visualization, computer vision, bio-inspired computing systems, power electronics, power systems, machine and motor drive, power management IC as well as inter-disciplinary areas involving information science and technology.
Compensation and Benefits:
Salary and startup funds are highly competitive, commensurate with experience and academic accomplishment. We also offer a comprehensive benefit package to employees and eligible dependents, including on-campus housing. All regular ShanghaiTech faculty members will join its new tenure-track system in accordance with international practice for progress evaluation and promotion.
Strong research productivity and demonstrated potentials;
Ph.D. (Electrical Engineering, Computer Engineering, Computer Science, Statistics, Applied Math, or related field);
A minimum relevant (including PhD) research experience of 4 years.