Teaching assistant - AI & Advanced Computing

Applications are invited for teaching assistant (TA) positions in the School of AI & Advanced Computing. The TA positions are open for all qualified interested graduate students (Masters and PhD students) on campus of XJTLU or other graduates in Suzhou. All applications will be considered by the recruiting panel which consists of two or more academic staffs in the Department.

TA duties include:

XJTLU Master’s students, XJTLU PhD students, and postgraduate (Master’s and PhD) students from other universities

• Laboratory demonstration and support for practical work in the classroom
• Attendance on and support with field courses
• Group tutoring
• Scheduled office hours for one-to-one tutoring
• Invigilation of formal examinations and/or class tests
• Marking of formative assignments with appropriate training
• Other appropriate activities as determined by academic units

At the discretion of relevant academic units, XJTLU PhD students may be permitted to undertake the following additional responsibilities with appropriate training and guidance:

• Delivery of occasional formal lectures and/or seminars within their area of expertise after having received appropriate training and initial supervision from their supervisor or the respective Module Leader. Such training might be provided by individual academic units, or the Education Development Unit (EDU). Relevant health and safety issues should be covered in this training.
• Assistance in marking of summative assessments with appropriate training and under the supervision of the module leader, subject to prior approval from the Head of the academic unit delivering the module. However, they must never act as the sole examiner on any summative assessment. All assessment tasks marked by XJTLU PhD students must be moderated, and they are not permitted to act as moderators.

Modules include:

DTS002TC Essentials of Big Data (Location: SIP)
Credits: 5
Delivery Mode: Lectures: 2*7, Seminars:2*7 ,
Labs: 4*7; Second Block
Number of TA needed: 8
Requirements: Proficient with Matlab

DTS101TC Introduction to Neural Networks (Location: TC)
Credits: 2.5
Delivery Mode: Lectures: 4*5,Seminars: 2*1 ,
Tutorials: 2*2; First block
Number of TA needed: 1
Requirements: Strong experience in deep
learning, machine learning, and Python

DTS104TC Numerical Methods (Location: TC)
Credits: 2.5
Delivery Mode: Lectures: 4*5, Seminars: 2*1 ,
Tutorials: 2*6;Second block
Number of TA needed: 2
Requirements: Good mathematical background and
experience with Matlab

CPT106TC Introduction to Databases (Location: TC)
Credits: 5
Delivery Mode: Lectures: 5*5, Seminars: 2*1,
Labs: 5*5; Second block
Number of TA needed: 3 to 4
Requirements: Good knowledge of database design
and SQL

DTS203TC Design and Analysis of Algorithms (Location: TC)
Credits: 5
Delivery Mode: Lecturers:8*5, Seminar：2*1, Labs: 1*6;First block
Number of TA needed: 2
Requirements: (1) knowledge of algorithms
(2) be able to implement algorithms with Python

DTS204TC Data Visualisation (Location: TC)
Credits: 2.5
Delivery Mode: Lectures: 4*5, Seminars:2*1;
Labs: 1*6;Second block
Number of TA needed: 2
Requirements: Be familiar with or interested in
Data Visualisation. Skills: JavaScript,D3.js

DTS205TC High performance computing (Location: TC)
Credits: 2.5
Delivery Mode: Lectures: 3*5, Seminars:2*1;Tutorial:
1*6, Labs: 1*6;First block
Number of TA needed: 2
Requirements: Familiar with Java if the
candidate is a PhD student, if familiar with both Java and Hadoop, master level
is fine.

DTS206TC Applied Linear Statistical Models (Location: TC)
Credits: 5
Delivery Mode: Lectures: 8*5, Seminars:2*1 ,
Tutorials: 1*6 Second block
Number of TA needed: 2
Requirements: Proficient in R

DTS304TC Machine Learning (Location: TC)
Credits: 5
Delivery Mode: Lectures: 4*5, Seminars: 2*1, Tutorials: 2*6, Labs: 2*6; Second block
Number of TA needed: 2
Requirements: Proficiency in Python programming language. Ideally, have a background in machine learning.

Skills and Knowledge

• Proficient spoken and written English
• Excellent communication and interpersonal skills
• Excellent presentations skills, and skillful in Microsoft Office Software (Word, Excel, PowerPoint, etc.)
• Excellent organizational skills and attention to detail
• Be adaptable and open to change
• Previous TA working experience preferred

The pay rate for Academic Year 2022-23

• XJTLU PhD students: RMB 60/hour (before tax)
• XJTLU Master’s students: RMB 50/hour (before tax)
• PhD and Master’s students from other universities: RMB 50/hour (before tax)

How to apply

Applicants should submit their application to AIAC@xjtlu.edu.cn by 8 February, 2023

Applicants are required to provide their CVs and academic transcripts of previous studies.