Assistant Professor of Teaching, Industrial Data Science

Lingnan University; Tuen Mun, Hong Kong; Vor Ort; HKD 600.000 - 900.000; Vollzeit

Benefits dieser Stelle

Annual leave

Medical and dental benefits

Mandatory Provident Fund

Gratuity

Incoming passage and baggage allowance

Zusammenfassung

Lingnan University invites applications for the position of Assistant Professor in the Division of Industrial Data Science. The appointee will teach postgraduate courses, coordinate seminars and capstone projects, and contribute to programme development that integrates arts, science and data-driven approaches.

The successful candidate will engage in teaching, scholarly activities and departmental service, and is expected to support student learning through workshops and seminars while performing

Qualifikationen

• PhD in data science, industrial engineering, computer engineering, computer science, artificial intelligence, information engineering or related fields.
• Experience teaching relevant courses and/or relevant professional or industrial experience.
• Strong command of English and Chinese (Putonghua included).

Aufgaben

• Teach postgraduate courses and coordinate/supervise seminars, tutorials and capstone projects.
• Engage in teaching, learning and scholarly activities.
• Contribute to planning, administration and development of programmes/courses.
• Organise student activities or training workshops to enhance learning experience.
• Undertake administrative duties related to academic and departmental affairs.
• Perform other duties as assigned by the Division leadership.

Kenntnisse

English proficiency

Chinese proficiency

Ausbildung

Doctoral degree in data science / industrial engineering / computer science

Jobbeschreibung

Lingnan University invites applications for the position of Assistant Professor in the Division of Industrial Data Science. The appointee will teach postgraduate courses, coordinate seminars and capstone projects, and contribute to programme development that integrates arts, science and data-driven approaches.

The successful candidate will engage in teaching, scholarly activities and departmental service, and is expected to support student learning through workshops and seminars while performing