Programme Manager (Centre for Advances in Reliability and Safety Limited)
Centre for Advances in Reliability and Safety Limited
Programme Manager (Ref. No.: CAiRS-PM/P4.1-3)
[Appointment period: twenty-four months initially; with possibility of further appointment]
The appointee will report to Programme Leader and assist in planning and monitoring research projects – “AI based safety assurance”, “Hybrid strategies for AI-based safety assurance” and “Functional safety verification of systems that implement AI”. He/she will be required to:
1) work with industry counterparts in consolidating academic research into tangible deliverables;
2) steer the project, and ensure good and appropriate applicability to commercial/industrial partners;
3) coordinate the delivery, installation and testing of the equipment; and ensure the equipment being properly installed, tested and commissioned at the Centre;
4) manage research and development activities including technical and financial aspects, and other project administrative tasks such as preparing project updates and reports;
5) apply for patents;
6) work closely with research colleagues of the teams;
7) coordinate with local and overseas universities, research institutions and business partners, and handle enquiries in a professional manner; and
8) perform any other duties as assigned by the Centre Director or his delegates.
1) have a doctoral degree in Industrial Engineering, Electrical Engineering, Mechanical Engineering or a relevant discipline;
2) have at least tens years of research/relevant work experience with knowledge of corporate product development;
3) be well-organized, capable to work under pressure and able to handle multi-tasking assignments in a multidisciplinary team;
4) have excellent interpersonal skills;
5) have a good command of written and spoken English and Chinese, with proficiency in Putonghua being an advantage.
Preference will be given to those with work experience in: a) leading data science, reliability, and safety projects; b) building and deploying large scale machine learning models, such as randomforest, xgboost, lightgbm, LSTM, Bert, etc.; and/or c) any big data and cloud solutions, such as HIVE, spark, Hadoop, Azure or AWS, etc.
A highly competitive remuneration package will be offered. Applicants should state their current and expected salary in the application.
Please send a detailed curriculum vitae via email to email@example.com
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