Part-time Research Assistant I/Research Assistant II/Technical Assistant (R at Open University of Hong Kong

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

05 Oct, 26

Salary

0.0

Posted On

07 Jul, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, MATLAB, C++, IoT, Arduino, Raspberry Pi, LoRa, ZigBee, NB-IoT, TensorFlow, Scikit-learn, R, Excel, Machine Learning, Data Analysis, Multi-physics Modeling

Industry

Higher Education

Description

Founded in 1989, Hong Kong Metropolitan University (HKMU) is a modern, vibrant and dynamic university. We tailor our professional programmes to adapt to market trends and meet industry needs, thus providing our students with quality professional education and clear career paths. Being the first University of Applied Sciences (UAS) in Hong Kong, we pledge to play a pioneering role in enhancing recognition of vocational and professional education and training, and nurturing talents with both applied skills and knowledge. As a faculty-driven, student-centred university in support of innovative teaching and learning, strategic research, and stakeholder outreach to provide maximum benefit to our communities, we conduct research that advances knowledge and enhances teaching, focusing on strategic areas, including digital humanities and literature, international business, gerontechnology, personalised care, smart city, open and innovative education, and bilingual learning and teaching. HKMU is becoming an ever more vital link in addressing and helping Hong Kong to solve many difficult challenges – as part of our involvement in, and commitment to, the ‘metropolis’ of Hong Kong. Our plans to expand into the Greater Bay Area (GBA) will also cultivate talent to serve Hong Kong and the wider metropolitan GBA. For more information about the University, please visit https://www.hkmu.edu.hk. We are now looking for a suitable person to fill the following position in the School of Science and Technology: Major Duties and Responsibilities The appointee will mainly assist the research team in a research project “Development of Using Retired Batteries from Electrical Vehicles to Build Smart Emergency Power Systems for Buildings in Hong Kon” (R6565). The appointee will be responsible mainly for the following: Designing and validating coupled multi-physics models for agrivoltaics-wind systems under subtropical microclimates; Deploying IoT-enabled smart monitoring systems for crops, livestock, and renewable energy generation; Implementing machine learning algorithms to optimize energy generation, agricultural productivity, and cost-efficiency; Conducting experiments and collecting data using IoT sensors (e.g., soil moisture, solar irradiance, wind speed); Optimizing resource allocation (e.g., sunlight, ventilation) between energy and agricultural outputs; Collaborating effectively with cross-disciplinary teams, including engineers, agronomists, and economists; and Maintaining detailed documentation of system configurations and operational procedures, and publishing research findings in peer-reviewed conferences and journals. Candidates Candidates should possess the following qualifications, experience and competence: At least 5 subjects with Level 2 in HKDSE or equivalent, including English & Chinese languages and Mathematics / Diploma (for Technical Assistant); A bachelor’s degree in Engineering (Electrical/Mechanical/Agricultural), Computer Science, Environmental Science, or a related discipline; (for Research Assistant II); A master’s degree in Engineering (Electrical/Mechanical/Agricultural), Computer Science, Environmental Science, or a related discipline; (for Research Assistant I); Candidates with prior research experience in IoT, renewable energy, or smart agriculture are highly desirable; Candidates with the following skills are preferred; Programming: Python, MATLAB, or C++ for modelling and data analysis; IoT & Hardware: Sensor networks, Arduino/Raspberry Pi, and wireless protocols (LoRa, ZigBee, NB-IoT); Data Analytics: Machine learning frameworks (TensorFlow, scikit-learn) and statistical tools (R, Excel); Domain Knowledge: Familiarity with photovoltaic systems, wind energy, and agricultural microclimates; Strong communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders; A strong sense of responsibility, coupled with effective organizational and interpersonal skills; and Proficiency in both English and Chinese. Terms and Conditions for Appointment Successful candidate will be appointed on a temporary part-time contract. Benefits will be provided in accordance with the statutory provisions. To Apply Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System. The personal data collected will be used for the purpose of considering your application for employment. For details, please refer to the “Personal Data (Privacy) Notice for Job Applicant” on the University’s website. If you are not contacted by the University within eight weeks from the closing date of application, you may assume that your application was unsuccessful.

Responsibilities

The appointee will design multi-physics models and deploy IoT-enabled monitoring systems for agrivoltaics-wind systems. They will also implement machine learning algorithms to optimize energy and agricultural productivity while publishing research findings.