Summer Research Internship

The Summer Research Internship provides opportunities for secondary school students to undertake engineering-related research attachments for approximately one month at CityU during the summer 2024. Students will be actively engaged in CityU laboratories under the supervision of CityU PhD students and a faculty member as an advisor.

During the internship, students will:

develop research skills and knowledge in a specific area of interest
join a world-class research team and work alongside with leading experts in the field
establish professional networks for future studies and career

Eligibility

Secondary 4 - 6 students
High proficiency in English with good academic standing
Nominated by a referee who is REQUIRED to be a current teacher at the secondary school attended by the student.

Key Dates

Schedule	Dates
Application Deadline	4 March 2024 (Monday)
Interview Period	25 March - 30 April 2024
Release of Result	by 15 May 2024 (Thursday)
Internship Duration	4 weeks in July - 16 August 2024 (min. 16 contact hours per week on CityU campus)
Submission of Logbooks & Presentation Videos Deadline	23 August 2024 (Friday), tentative

Application

Students are required to complete the online application form and provide contact details of their referees.

Online Application

We will acknowledge receipt of your applications by email.

If you have any enquiries, please contact us by phone at 3442 2770 or email to BFEngg.Hub@cityu.edu.hk.

Department	Code	Research Topic	Description
Architecture and Civil Engineering	ACE-S1	Built-informatics and Smart Cities Cluster: The Access to the Metaverse of Digital Architecture and Engineering	Students will gain a better understanding of architecture and engineering through this research internship. Digital tools inside the BIM lab will allow students to explore digitalisation in construction and learn basic 3D modelling theories. Students will research innovative designs and create VR models through hands-on tutorials.
Biomedical Engineering	BME-S1	Learn Microfluidics with Fun	Students will be involved in the design, fabrication and characterization of their own microfluidic devices through hands-on workshops and a project showcase.
Computer Science	CS-S1	AI Painting	Students will learn AI tools for painting, including Stable diffusion and ControlNet, to create their own artworks using different modalities of control, such as text prompting, sketching, and layout design. Additionally, students will have the opportunity to learn AI tools for animating images and creating their own animations.
Electrical Engineering	EE-S1	State Key Lab Research Summer Internship	Students will gain valuable learning experience at the State Key Laboratory of Terahertz and Millimeter Waves, City University of Hong Kong, to perform research activities in the area of antenna design, communication design, software and hardware designs.
Mechanical Engineering	MNE-S1	LLM-based Visual Navigation System in Complex Crowded Area	With the success development of Robotics and LLM (ChatGPT), we see a new future via combining robotic operation and the common-sense ability of LLM. In this project, we will leverage the great generative ability of ChatGPT to assist robot in visual navigation of complex crowded area. Which is hard decades ago but possible now.
	MNE-S2	Pedestrian Detection for Mobile Robots	Students will join the CityU Autonomous Systems Lab (ASL) as junior members to gain some insight into robotic research. Pedestrians are common obstacles for mobile robots. This project will use a 2-D LiDAR to detect pedestrians. The algorithm will be deployed on a real mobile robot with a 2-D LiDAR sensor.
	MNE-S3	2D metallic and ceramic nanomaterials: From fabrication, characterization to applications.	In this project, students will gain hands-on experience in fabricating 2D metallic and ceramic nanomaterials using the cutting-edge technique developed at CityU. They will be guided by their academic advisors to characterize the mechanical, physical, and chemical properties of these materials using state-of-the-art techniques. This comprehensive understanding will enable students to apply the fabricated 2D materials to various real-world applications within the broad field of mechanical and materials engineering.
Materials Science and Engineering	MSE-S1	Advanced Materials for High-Performance Rechargeable Batteries in the Post-Lithium-Ion Batteries Era	Students will participate in the R&D project related to future materials for high-performance rechargeable batteries as an intriguing alternative for use as the coming post-lithium-Ion batteries. New materials to be explored include the cathode, anode, and electrolyte. Solid electrolytes may be one of the focuses.
Systems Engineering	SYE-S1	Prototypes for Smart Cities and Smart Manufacturing	Students will join our research teams to design, develop, and test various prototypes for smart city and smart manufacturing system design and management.
	SYE-S2	Reliability Study of High Performance Microelectronic Chips	Students are welcomed to join our research teams and study the reliability issues for high-performance microelectronics that can be applied in a data center for AI calculations.
	SYE-S3	Building Structural Digital Twin of Critical Urban Assets	Students will join our research group to build a structural digital twin of a critical urban asset in smart city.
	SYE-S4	Intelligent Vehicle Trajectory Reconstruction Summer Internship	Students will learn Python programming and apply their skills to real-world data. They will source online videos and footages of traffic incidents and use mathematical modeling and computer vision to reconstruct and interpolate vehicle trajectories from the sourced videos. The insights gained from this project will be helpful in designing controllers for autonomous vehicles.
	SYE-S5	Development of New Methods for 3D Display and 3D Industrial Enspection	Students will join our research team to design and develop new methods for 3D display, holograms, and 3D imaging applications that can be used in a smart city
	SYE-S6	Smart Cloud Detection and Forecast Model	In weather analysis and forecasting, especially in the prevention of severe weather events, clouds play a crucial role. However, due to the chaotic nature of weather systems, cloud prediction is challenging. Building a cloud recognition and prediction model based on new deep learning models and satellite images holds significant application significance.
	SYE-S7	Advanced electronic Thin Film Materials Preparation and Characterization	Students are welcome to join our research group and study the manufacturing of advanced electronic thin film for high-performance integrated circuits that can be applied in future computing.