The appointee will be responsible to assist with the administrative and coordination of the research project. Tasks include: (a) making arrangement to ensure a smooth research study; (b) collecting data and conducting data analysis; (c) preparing reports; and (d) performing other assigned duties.

Applicants should have (i) a bachelor's degree in nursing, health science, gerontology, mental health or psychology; (ii) 3-4 years of research experience and knowledge of qualitative research; and (iii) some working experiences in gerontology and long-term care settings.

The appointee will assist the Principal Investigator in all research related activities, include (i) arranging and conducting survey questionnaires, interviews & focus groups with parents; (ii) conducting data analysis of the quantitative data and qualitative verbatim transcription; (iii) assisting in drafting operational manuals, forms, templates and reports; (iv) drafting research manuscripts for presentation/publication in conferences/journals; (v) performing other tasks as assigned.

Applicants should have (i) a Bachelor's degree, preferably with a Master's/MPhil degree in Social Sciences or a related discipline; (ii) solid training and experience in research methods, using SPSS software; (iii) excellent English and Chinese proficiency.

Salary will be commensurate with qualifications and experience.

The appointee will be responsible for assisting the research of ISG project: UAV-aided network intelligence techniques for disaster management [ISG210101].

The tasks include algorithm design, training data preparation, implementing the designed algorithms and so on. Appointment will be made on a contract basis for 3-12 months commencing at earliest convenience.

Applicants should (i) have a bachelor's degree or above in Computer Science, Information Technology or related disciplines; (ii) have experience in algorithm design, computer network, or deep learning and be able to work independently; (iii) have good communication and interpersonal skills. Applicants with publication experience are preferred.

The appointee will be responsible for assisting the research of Artificial Intelligence Research project (ITBG190103). 

Apart from conducting researches, securing external research grants, and undertaking research and scholarly tasks as the main duties, the appointee shall also be responsible for teaching in related areas, and other assigned duties.  

Applicants should have (a) an earned and recognized Doctorate degree in either nursing, health sciences, mental health, psychology or relevant disciplines; (b) previous experiences in handling qualitative research or in gerontology and long-term care, and healthcare issues, and (c) relevant teaching / professional / research experiences. Preference will be given to those with doctoral degree having teaching experience in degree programmes / proven research record. Less experience will be considered as Research Associate / Research Assistant.

The appointee, as the "Centre Manager", will assist the Centre Director to oversee the daily operations of the Caregiver Research & Development Centre (CRC). Tasks will include:

• identify resources and assist to prepare and write up research or service project proposals,
• conduct research studies (quantitative and qualitative), and service projects on caregiving,
• conduct data analysis of the quantitative data and qualitative verbatim transcription independently,
• organize workshops, seminars, international conferences and other academic-related events,
• draft research manuscripts and powerpoints for publication / presentation in journals / conferences, as well as prepare teaching materials, manuals, forms, template and reports,
• communicate/liaise with collaborating organizations and experts,
• lead and supervise RAs and student helpers to carry out various tasks,
• assist the Centre Director to carry out financial management of and resource acquisition for the CRC,
• performing other tasks as assigned.

Applicants should have

• A Master degree, preferably a PhD degree, in Social Sciences or a related field,
• At least 5 years of relevant research experiences,
• Proficiency and experiences in quantitative and qualitative data analysis,
• Excellent proficiency in oral and written English and Chinese,
• an ability to work independently & competently,
• Experiences in supervising or working with other research staff.

The appointee will be responsible to assist staff members within the School to conduct administrative and coordinating research activities and research projects. Tasks include: (a) literature search, (b) coordinating research work, (c) collecting data and conducting data analysis; (d) preparing reports; and (e) performing other duties as assigned.

Applicants should have (i) at least a bachelor's degree in nursing, health science, allied health backgrounds, or statistics-related qualifications; (ii) 3-4 years of research experience and knowledge of quantitative research, and prior experience of conducting statistical analysis are preferred.

The appointee will assist in research activities for one of the following funded FDS research projects:

Developing Efficient Cartoon Animation Editing Pipeline via Deep Entity Recognition and Motion Analysis [UGC/FDS11/E02/23]

A Transformer-based Method for Refining and Abstracting Sketches at Different Levels of Details [UGC/FDS11/E02/24]
 

Typical tasks will include, but are not limited to:

1. Preparing and annotating training datasets;
2. Implementing and optimizing proposed deep learning algorithms;
3. Conducting ablation analysis and comparative experiments;
4. Organizing and performing user studies and evaluations; and
5. Documenting results and preparing technical reports and manuscripts.

1. Bachelor's degree or above in Computer Science, Information Technology, or related disciplines;
2. Research experience in deep learning, computer vision, or image processing, with proven ability to work independently;
3. Competency in developing deep learning models using standard libraries and frameworks such as PyTorch or TensorFlow;
4. Good communication, interpersonal skills, and teamwork spirit; and
5. Publication experience in peer-reviewed conferences or journals is desirable but not mandatory.