Lecturer in Data Science / Computer Science at NUIST-Reading Academy

The NUIST-Reading Academy is located in Jiangsu Province of China, and is a joint venture between the University of Reading, UK, and NUIST, China. The Academy aims to provide high quality education to students in China with the possibility of completing degree courses in the UK. It currently offers seven undergraduate programmes: Applied Chemistry, International Economics and Trade, Mathematics and Applied Mathematics, Environmental Engineering, Atmospheric Science, Geographic Information Science, and Data Science and Big Data Technology.

There are a variety of central support facilities from the Academy to assist research and training initiatives including training opportunities provided by the Centre for Quality, Support and Development (CQSD) from the University of Reading. We also offer a supportive environment where you will meet a community of academics from both the University of Reading and NUIST who are dedicated to delivering high quality teaching and research.

The post is based in the modern city of Nanjing, capital of Jiangsu province, with easy access to public transportation, international airports, convenient stores, hospitals etc.

Job particulars:

• One full-time Data Science / Computer Science lecturer post at NUIST.
• Annual salary (RMB, before tax): 250,000+, depending on relevant individual skills and experience.
• Travel allowance: 10,000 RMB per year.
• Accommodation provided.
• Medical Insurance.
• Starting date: February 2022.

Responsibilities:

The NUIST-Reading Academy delivers all courses in English. The dual-degree curriculum is designed and developed by the University of Reading. Instruction and assessment take place at the Academy. The appointee will support students on the dual-degree programme and work as part of a close-knit team.

The appointee will have the following main responsibilities:

• Contribute to and enhance teaching on the BSc Data Science / Computer Science with specific responsibility to cover core-teaching requirements and contribute to other teaching as agreed with the NUIST-Reading Academy administration;
• Assessment, grading and feedback of written work and oral presentations;
• Hold weekly office hours;
• Communicate effectively with students and staff;
• Maintain friendly and effective working relationships;
• Participate in appropriate professional meetings and workshops;
• Organizing extra-curriculum learning activities for students;
• Motivating students to engage in learning, and help them to improve the quality of their work.

Person Specification

Essential

• Advanced level of proficiency and communicative competence in English;
• PhD in Data Science and/or Computer Science;
• Experience of teaching Data Science and/or Computer Science; and/or related disciplines at undergraduate level;
• Experience of the administration of courses and modules in British / Western universities;
• Excellent organisation, communication and inter-personal skills;
• Ability to work under pressure;
• An excellent team player;
• A willingness to work flexibly as required.

Desirable

• Experience of teaching undergraduate students various levels of Data Science in a Chinese university environment;
• Documented excellence in classroom teaching;
• Documented excellence as an academic and career advisor to college students;
• Experience addressing needs of students from diverse backgrounds and cultures;
• Experience with assessment of student learning and programme evaluation and coordination;
• Evidence of professional publications and/or presentations in Data Science research;
• Enthusiasm for one’s field and a commitment to staying current.

Application instructions:

Interested applicants should submit a cover letter detailing how they satisfy the outlined requirements, a current resume, a statement of teaching philosophy, and a list of at least three (3) professional references.

Application materials should be sent to Dr Jin Zhou at zhoujin@nuist.edu.cn, copying to: Mr Hugh Xu Wang at hugh-wangxu@qq.com and be in Word or PDF format.