Internship

Build prototype systems for cross-modality sensing using wireless and acoustic signals

• Proficient with Python and C/C++ programming

• Experience with embedded/mobile systems development
• Background in wireless systems and signal processing

Application Deadline: June 30, 2023 (Friday)
To apply, please email your CV to Dr. WU Chenshu (chenshu@cs.hku.hk).

3 - 6 months

• Proficient with Matlab and/or Pytorch
• Be familiar with basic knowledge of Schrodinger equations

• Master's degree or above in computer, communication, software engineering, mathematics, artificial intelligence, and other related majors;
• Familiar with the Python development language and understand the Spark framework;
• Proficiency in using one or more of Tensorflow, Keras, and PyTorch open source frameworks;
• Understand and be able to use the most cutting-edge algorithms of deep learning;
• The algorithm in the paper can be reproduced independently;
• Priority conditions:
  • Implementation experience using Java, and SQL Coding experience of Python and bootstrap is an advantage;
  • Experience with Spring Framework, Docker/Kubernetes, Kafka, Spark, HBase, and Redis is a plus;
  • Good command of written and spoken English or Mandarin

2023 Summer

To apply, please email your CV to Ms Cecilia Tam (cecilia.tam@tcl.com)

• Bachelor or above in STEM-related discipline such as Computer Science, data science, Electronic Engineering, Information Engineering, Mathematics or relevant discipline
• The candidate should be interesting in the field of computer vision, image processing and machine learning, multi-media A/V processing
• Experience in programming using C++/Python
• Experience in image processing or machine learning, or deep learning model development
• Preferred:
  • Experience in deep learning frameworks (OpenCV, TensorFlow, Caffe, PyTorch)
  • Experience in below areas: defect detection/segmentation, super-resolution, image enhancement, audio processing, etc.

2023 Summer

To apply, please email your CV to Ms Cecilia Tam (cecilia.tam@tcl.com)

• Hold a B.Sc degree or above with a major in Electrical/Electronics Engineering, Computer Science, Computer Engineering, or a related discipline
• Hands-on experience with Python, PyTorch, and Linux
• Good understanding of Audio Signal Processing, Machine Learning, and Deep Learning
• A track record of original scientific publications and conference contributions would be a plus

2023 Summer

To apply, please email your CV to Ms Cecilia Tam (cecilia.tam@tcl.com)

• With a focus on “Energy-efficient machine learning for IoT”
• Research and development of machine learning algorithms on IoT devices

• Proficient with python and/or C  programming
• Experience in machine learning 

• Proficient with Matlab and/or Pytorch
• Be familiar with basic knowledge of Schrodinger equations

• Able to build a machine/deep learning pipeline
• Familiar with Pandas, PyTorch, or Tensorflow

Preferred:

• Major in Computer Science/Math/Statistics/EE or other related concentration
• Experience in Reinforcement Learning, Recommendation System
• Strong programming skills
• Strong analytical ability when solving practical problems

Open all year round

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Major in STEM-related discipline such as Computer Science, data science, Electronic Engineering, Information Engineering, Mathematics or relevant discipline
• Interesting in the field of computer vision, image processing and machine learning
• Experience in programming using Python/C++ 
• Experience in image processing, or machine learning, or deep learning model development 

Preferred:

• Experience in deep learning frameworks (Tensorflow, Caffe, PyTorch, Keras) 
• Experience in below areas: super-resolution, image enhancement, etc

Open all year round

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Major in Computer Science, Robotics, or related field
• Experience in C++ and Python development 
• Familiarity working within a Linux environment 

Preferred :

• Experience in ROS 
• Familiar with laser-slam or visual-slam, cartographer, gmapping, hector, orb-slam 

Open all year round

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Ph.D degree with strong mathematical modeling and algorithm skills in engineering, operations research and optimization, computer and other applied sciences
• Familiar with various types of operational research optimization models, understand the usage scenarios and computing efficiency of each model, and be able to select appropriate algorithm models to meet customer needs
• Have a certain engineering ability, can abstract and standardize models, algorithms, and scenarios, and have the ability to wrap code
• Specialize in at least one of the following programming languages ​​(C/C++, C#, Java, Python)
• Have strong communication skills, learning ability, self-driving ability, sense of responsibility and teamwork ability

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Master or above in STEM-related discipline such as Computer Science, data science, Electronic Engineering, Information Engineering, Mathematics or relevant discipline
• Interesting in the field of computer vision, image processing and machine learning
• Experience in programming using Python/C++
• Experience in image processing, or machine learning, or deep learning model development

Preferred:

• Experience in deep learning frameworks (OpenCV, TensorFlow, Caffe, PyTorch, Keras)
• Experience in below areas: defect detection/segmentation, super-resolution, image enhancement, etc

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Master's or PhD in Computer Science, Statistics, and other related majors
• Excellent coding ability, solid data structure, and algorithm skills
• Solid programming skills, familiar with programming languages such as python and scala
• Hands-on industry experience in big data processing filed such as Spark, HIVE, Elasticsearch, Redis etc
• Familiar with deep learning frameworks such as Tensorflow and Pytorch, as well as commonly used machine learning algorithms and recommendation algorithms
• Minimum 1-2 years working experience in machine learning, and data mining-related fields, and excellent graduates are also welcome
• Excellent problem analysis and problem-solving skills, passion for solving challenging problems
• Enthusiastic about technology, good communication skills, and team spirit.

Plus :

• Experienced in the propensity model and causal inference is preferred
• Familiar with one or more recommendation algorithms, and practical experience in recommendation systems, search engines, and other related fields are preferred

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com)

• Programming skill is required;
• Major in Mathematics, Statistics, AI, Computer Science and the related disciplines.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Professor Ng (mng@maths.hku.hk) by the application deadline.

• Solid programming skills in C, C++, Java, or Python.
• Optional:
  • experience in large system development, data analytics platform (e.g., Tableau) and research.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Professor Cheng (ckcheng@cs.hku.hk) by the application deadline.

Proficient with Python and Pytorch

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Dr. Qi (xjqi@eee.hku.hk) by the application deadline.

Assisting the postdoctoral research to conduct an AI-based automatic identification project. 

Works may include code writing and operation, data analysis, photo taking, microscopic work.

• Major in a relevant field such as statistics/mathematics, computer & coding skills (eg Python, MATLAB, R);
• Experience in AI and automatic identification. 

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Dr. Yasuhara (yasuhara@hku.hk) by the application deadline.

TV recommender system in TCL provides recommendations for movies, albums, TV dramas, etc. to users who buy TCL TVs.

By collecting viewing history data over a period of time, recommendation mechanisms developed with deep learning and reinforcement learning can help users access the TV programs of their choice.

Diversification of the recommendation results list has become one of the leading topics of recommender system research to optimize users' experience with the recommendation system. 

Diversification of the recommendation results list has become one of the leading topics of recommender system research to optimize users' experience with the recommendation system. 

You will be working on designing and developing ML or DL models to enhance the diversification performance on our productive TV recommendation system.

Responsibilities:

• Implement ML or DL prototype models; 
• Reproduce models of research papers;
• Fill out papers or patents for research output.

• Ability to design and train deep learning models and other machine learning techniques using Python;
• Familiarity with Scikit-Learn, PyTorch, or Tensorflow.

Preferred:

• Major in Computer Science/Math/Statistics/EE or other related concentration;
• Experience in Reinforcement Learning, Recommendation System; or familiarity with Reinforcement Learning, Blackbox Optimization/Bayes Optimization is a plus;
• Solid programming skills;
• Strong analytical ability when solving practical problems.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

TCL CSOT is one of the largest display manufacturers in China, and displaying material discovery is the key to displaying innovation.

Traditional experiments and computational modelling often consume tremendous time and resources and are limited by their experimental conditions and theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials.

Recently, materials discoveries using machine learning have been receiving increasing attention and have led to great improvements in both time efficiency and prediction accuracy.

You will be working on cutting edge interdisciplinary problems in machine learning and material science.

Machine learning has demonstrated its strong power in the exploration and development of many materials. In discovering and optimizing some highly complicated material systems, traditional approaches are powerless, but AI models provide a way to accelerate this process.

Responsibilities:

• Implement ML or DL prototype models;
• Reproduce models of research papers;
• Fill out papers or patents for research output.

• Ability to design and train deep learning models and other machine learning techniques using Python;
• Familiarity with Scikit-Learn, PyTorch, or Tensorflow.

Preferred:

• Major in Computer Science/Math/Statistics/EE or other related concentration;
• Experience in Reinforcement Learning, Recommendation System; or familiarity with Reinforcement Learning, Blackbox Optimization/Bayes Optimization is a plus;
• Solid programming skills;
• Strong analytical ability when solving practical problems.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

The demand for multimodality interaction with different types of technical products, including televisions, is increasing. TV devices have already brought new experiences to users by adding the input of voice control, rather than the traditional single-mode remote control.

In the future, user needs will be met in other innovative ways, e.g., gestures, eyeball tracking, and so on. This multimodality interaction will bring users a brand-new experience and make life more convenient. The multimodality interaction project team aims to design such innovative interaction methods, and plans to apply them to TCL smart TVs in the future. In this internship program, you will join the project team to develop a multimodality interactive prototype system for smart TVs.

• According to the requirements document, develop the Android app with the team, and optimize the performance and effects of the app;
• Output the development summary document.

• Major in Computer Science/Math/Statistics/Electrical and Electronic Engineering or other related concentration;
• Proficient in programming on C/C++, Java, Python or Matlab;
• Advanced troubleshooting abilities;
• Team worker and self‐motivated;
• A good passion for new technologies and innovations.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

Super-resolution (SuperRes) is an algorithm for upgrading and improving the details of an image: a high-resolution image is reconstructed through one or more frames of low-resolution images. Currently, TCL Hong Kong Research Centre is developing SuperRes that combines AI methods and traditional image processing methods, and plans to apply it to TCL smartphones. In the internship project, you will join the SuperRes project team and will be responsible for optimizing, testing and verifying the SuperRes algorithm and models. 

Through this internship program, you will learn the most advanced image processing algorithms, and experience the industry development process.

• Optimize the SuperRes model and related algorithms on mobile platform;
• SuperRes test and verification.

• Major in Computer Science/Math/Statistics/Electrical and Electronic Engineering or other related concentration;
• Proficient in programming on C/C++, Java, Python or Matlab;
• Advanced troubleshooting abilities;
• Team worker and self‐motivated;
• A good passion for new technologies and innovations.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

We will develop the super night scene camera function on a TCL smartphone, named SuperNight. The project aims to generate high-brightness, low-noise, true-color, and detailed results, significantly improving the quality of photos taken in low-light environments. 

You will work with the SuperNight project team and will be responsible for optimizing algorithms and models and collecting data. Through this internship program, you will learn the most advanced image processing algorithms, and experience the industry development process.

• Data collection for SuperNight training dataset, including data alignment and data verification;
• Optimize the SuperNight model and related algorithms on mobile platform.

• Major in Computer Science/Math/Statistics/Electrical and Electronic Engineering or other related concentration;
• Proficient in programming on C/C++, Java, Python or Matlab;
• Advanced troubleshooting abilities;
• Team worker and self‐motivated;
• A good passion for new technologies and innovations.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

The production line of TCL semiconductor display panels is 95% automated. However, product and equipment abnormality detection still relies on manual judgment and processing. There are a large number of quality inspection pictures which are generated every day (>=40000 pictures/day/production line).

The manual detection cannot fully cover malfunctions and defects, and there will be misjudgements. In terms of economic costs/benefits, high manual participation costs large manpower for enterprises because of the long cycle training and high turnover rate. Therefore, it is necessary to implement an intelligent and automated product inspection solution for semiconductor display products.

• Explore an industrial anomaly detection algorithm with strong versatility. The algorithm model requires easy manual parameter tuning and easy migration to different tasks.
• No limitation on the methods:
  • 1) Generate adversarial models, convolutional autoencoders, pre-trained neural network features and other deep learning models;
  • 2) Traditional image methods (generality and an absence of complicated manual tuning process are required).

• In-depth understanding of CNN, GAN, AutoEncoder and others; a strong interest in self-supervised learning and transfer learning research;
• Ability to analyse and tune deep learning models, use pre-training networks to extract common features, and perform visual analysis on features;
• Proficiency in using TensorFlow or PyTorch for algorithm development and model training, and an understanding of traditional image feature extraction methods.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

Our Computer Vision research team works on innovative problems that will power the next-generation automated vision inspection systems for a variety of industrial and manufacturing applications.

The research problems require exploring cutting-edge algorithms including self-supervised learning, transfer learning, domain adaptation, etc. to learn visual representations for industrial vision inspection systems.

• Work with research scientist and contribute research that can be applied to TCL product development;
• Prototype cutting-edge technologies for in-house use cases;
• Contribute to relevant research communities by producing publications and open-sourcing code.

12 to 16 weeks with Summer start dates.

Internships will be awarded on a rolling basis, candidates are encouraged to apply early. 

• Pursuing a Ph.D. or Master’s in computer science/math/statistics or other related concentration;
• Extensive knowledge of machine learning, computer vision, video understanding, machine learning and system, statistics, graph learning and/or NLP;
• Ability to work independently; 
• Ability to generate new ideas and innovate in an academic research setting; 
• Strong teamwork and communication skills; 
• Plus: Peer-reviewed research publication(s) at top conferences.

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

Our Multi-Modal Video Understanding team works on innovative problems that will power the next generation of products and platforms at scale.

The problems range across various research domains and we are looking for interns to explore new ideas in the area of multi-modal video understanding to help us better understand our video content. 

• Work with research scientist and contribute research that can be applied to TCL product development;
• Prototype cutting-edge technologies for in-house use cases;
• Contribute to relevant research communities by producing publications and open-sourcing code.

12 to 16 weeks with Summer start dates.

Internships will be awarded on a rolling basis, candidates are encouraged to apply early. 

• Pursuing a Ph.D. or Master’s in computer science/math/statistics or other related concentration.
• Extensive knowledge of machine learning, computer vision, video understanding, machine learning and system, statistics, graph learning and/or NLP. 
• Ability to work independently. 
• Ability to generate new ideas and innovate in an academic research setting. 
• Strong teamwork and communication skills. 
• Plus: Peer-reviewed research publication(s) at top conferences. 

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

Our Efficient ML team works on machine learning systems that require guarantees to adhere to necessary resource efficiency constraints.

We are seeking exceptional interns with a background in Deep Learning Acceleration, Computer Architecture, Hardware/Software Co-design of Accelerator Systems, and/or Federated Learning to work on designing efficient Deep Learning-based solutions that enable on-device execution for latency, power efficiency and privacy

• Work with research scientist and contribute research that can be applied to TCL product development;
• Prototype cutting-edge technologies for in-house use cases;
• Contribute to relevant research communities by producing publications and open-sourcing code;

12 to 16 weeks with Summer start dates.

Internships will be awarded on a rolling basis, candidates are encouraged to apply early. 

• Pursuing a Ph.D. or Master’s in computer science/math/statistics or other related concentration;
• Extensive knowledge of machine learning, computer vision, video understanding, machine learning and system, statistics, graph learning and/or NLP; 
• Ability to work independently;
• Ability to generate new ideas and innovate in an academic research setting; 
• Strong teamwork and communication skills;
• Plus: Peer-reviewed research publication(s) at top conferences. 

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

Our Platform Understanding team works on innovative problems that will power the next generation of products and platforms at scale.

The intern project will focus on state-of-the-art NLP and GNN techniques to create and understand a large-scale heterogeneous entity and text graph, as well as to explore its application to real-world search and recommendation systems. 

• Work with research scientist and contribute research that can be applied to TCL product development;
• Prototype cutting-edge technologies for in-house use cases;
• Contribute to relevant research communities by producing publications and open-sourcing code.

12 to 16 weeks with Summer start dates.

Internships will be awarded on a rolling basis, candidates are encouraged to apply early. 

• Pursuing a Ph.D. or Master’s in computer science/math/statistics or other related concentration;
• Extensive knowledge of machine learning, computer vision, video understanding, machine learning and system, statistics, graph learning and/or NLP;
• Ability to work independently;
• Ability to generate new ideas and innovate in an academic research setting; 
• Strong teamwork and communication skills;
• Plus: Peer-reviewed research publication(s) at top conferences. 

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.

• Work with research scientist and contribute research that can be applied to TCL product development;
• Prototype cutting-edge technologies for in-house use cases;
• Contribute to relevant research communities by producing publications and open-sourcing code.

12 to 16 weeks with Summer start dates.

Internships will be awarded on a rolling basis, candidates are encouraged to apply early. 

• Pursuing a Ph.D. or Master’s in computer science/math/statistics or other related concentration;
• Extensive knowledge of machine learning, computer vision, video understanding, machine learning and system, statistics, graph learning and/or NLP;
• Ability to work independently;
• Ability to generate new ideas and innovate in an academic research setting;
• Strong teamwork and communication skills;
• Plus: Peer-reviewed research publication(s) at top conferences. 

Application Deadline: April 25, 2021 (Sunday)

To apply, please email your CV to Ms. Cecilia Tam (cecilia.tam@tcl.com) by the application deadline.