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¾ßÌ幤×÷µØµã: | Ïã¸Û | н½ð: | Ãæ̸ | ѧÀúºÍÑо¿·½Ïò: | ¹¤³Ì£¬¼ÆËã»ú£¬Êýѧ | ÕÐƸ¸Úλ: | ²©Ê¿ºóºÍÑо¿ÖúÀí | ¹«Ë¾Ãû³Æ: | Ïã¸ÛÀí¹¤´óѧ | ¹«Ë¾ÍøÖ·: | www.polyu.edu.hk | ÁªÏµ·½Ê½: | siqi.bu@polyu.edu.hk |
HONG KONG POLYTECHNIC UNIVERSITY
Centre for Advances in Reliability and Safety (CAiRS)
(1) Postdoctoral Fellow (Ref. No.: CAiRS-R11/P3.3)
[Appointment period: thirty-six months]
(2) Research Assistant (Ref. No.: CAiRS- R12/P3.3)
[Appointment period: thirty-six months, with a possibility to become PhD candidate during employment]
Duties:
The appointees will assist the project leader in the research project - ¡°Forecasting maintenance¡±. The project will develop AI-based prognostic techniques to assess the extent of degradation from normal condition and enable the predictive maintenance actions for smart grid and building equipment.
Qualifications:
Applicants for the post of Postdoctoral Fellow should have a doctoral degree from either a local university or a well-recognised non-local institution1 in Engineering, Computer Science, Mathematics or an equivalent qualification in a related field and must have no more than five years of post-qualification experience at the time of application. They should also have a strong analytical skill with interests in big data and artificial intelligence.
Applicants for the post of Research Assistant should have a good bachelor/master degree awarded by a local university in Engineering, Computer Science, Mathematics or a related field.
For both posts, applicants should also have:
(a) proficiency in database software and programming language (e.g. MySQL, Python);
(b) good interpersonal and communication skills; and
(c) a good command of written and spoken English.
Preference will be given to those with research experience in machine learning and data science.
Applicants are invited to contact Dr Siqi Bu via email siqi.bu@polyu.edu.hk for further information.
Remuneration:
A highly competitive remuneration package will be offered. Applicants should state their current and expected salary in the application.
Notes:
Well-recognised non-local institutions refer to those that are among the top 100 institutions for STEM-related
subjects in the latest publication of world university ranking tables, including the Quacquarelli Symonds World
University Rankings, Shanghai Jiao Tong University (Academic Ranking of World Universities) or Times
Higher Education World University Rankings.
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