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HKU-TCL Joint Research Centre for Artificial Intelligence

Internship

internship concept

 

 

The HKU-TCL Joint Research Centre for Artificial Intelligence is now inviting applications for 15 different Internship Programmes, under either the research projects funded by the Centre or TCL Corporate Research (Hong Kong) Co., Ltd.

 

Programmes under Research Projects funded by the Centre:
Principal Investigator (PI): Professor NG Michael Kwok Po
Nature of WorkTo work with existing AI and machine learning projects with TCL
Duration of Internship2 - 3 months
Number of Places1 - 2
Requirements
  • Programming skill is required;
  • Major in Mathematics, Statistics, AI, Computer Science and the related disciplines.
AssessmentEvaluation will be conducted by the supervisor when the Internship is ended.
SalaryHK 8,000 per month
Application

Application Deadline: April 25, 2021 (Sunday)

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

Principal Investigator (PI): Professor CHENG Reynold Chun-Kong
Nature of WorkTo assist TCL engineers and PhD students in experiments and software development for the project on knowledge-graph-based query recommendation.
Duration of Internship3 - 6 months
Number of Places1 - 2
Requirements
  • Solid programming skills in C, C++, Java, or Python.
  • Optional:
    • experience in large system development, data analytics platform (e.g., Tableau) and research.
AssessmentEvaluation will be conducted by the supervisor when the Internship is ended.
SalaryN/A
Application

Application Deadline: April 25, 2021 (Sunday)

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

Principal Investigator (PI): Dr. QI Xiaojuan
Nature of WorkResearch and development on Moire pattern removal in images and videos.
Duration of Internshipmore than 6 months
Number of Places1 - 2
Requirements

Proficient with Python and Pytorch

AssessmentEvaluation will be conducted by the supervisor when the Internship is ended.
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

Principal Investigator (PI): Dr. YASUHARA Moriaki
Nature of Work

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.

Duration of Internship6 months
Number of Places1
Requirements
  • Major in a relevant field such as statistics/mathematics, computer & coding skills (eg Python, MATLAB, R);
  • Experience in AI and automatic identification. 
AssessmentN/A
SalaryUpon further discussion
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

Programmes under TCL Corporate Research (Hong Kong) Co., Ltd.:
  1. Improving Diversity in Recommendation System
  2. Accelerate Material Discovery with Meta-learning Bayesian Optimization

 

1. Improving Diversity in Recommendation System
Project Background

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. 

Nature of Work

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.
Duration of Internship2 - 6 months
Number of Places1 - 2
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 
2. Accelerate Material Discovery with Meta-learning Bayesian Optimization
Project Background

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.

Nature of Work

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.
Duration of Internship2 - 6 months
Number of Places1 - 2
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

  1. Multimodality interaction application development
  2. SuperRes application development
  3. SuperNight application development

 

1. Multimodality interaction application development
Project Background

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.

Nature of WorkIn this project, you will join the project team:
  • 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.
Duration of Internship2 - 6 months
Number of Places1 - 2
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

2. SuperRes application development
Project Background

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.

Nature of WorkIn this project, you will join the project team:
  • Optimize the SuperRes model and related algorithms on mobile platform;
  • SuperRes test and verification.
Duration of Internship2 - 6 months
Number of Places1 - 2 
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

3.  SuperNight application development
Project Background

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.

Nature of WorkIn this project, you will join the project team:
  • Data collection for SuperNight training dataset, including data alignment and data verification;
  • Optimize the SuperNight model and related algorithms on mobile platform.
Duration of Internship2 - 6 months
Number of Places1 - 2 
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

Product Inspection Solution Development for Semiconductor Display 
Project Background

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.

Nature of WorkProject Tasks:
  • 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).
Duration of Internship6 months
Candidates are encouraged to apply early.
Number of Places1 - 2
Requirements
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

  1. Computer Vision
  2. Video Understanding
  3. On-Device AI
  4. Deep Learning for Graphs
  5. Applied Machine Learning

 

1. Computer Vision
Project Background

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.

Nature of Work
  • 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.
Duration of Internship

12 to 16 weeks with Summer start dates.

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

Number of Places1 - 2 
RequirementsRequired Skills:
  • 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.
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

2. Video Understanding
Project Background

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. 

Nature of Work
  • 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.
Duration of Internship

12 to 16 weeks with Summer start dates.

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

Number of Places1 - 2
RequirementsRequired Skills:
  • 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. 
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

3. On-Device AI
Project Background

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

Nature of Work
  • 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;
Duration of Internship

12 to 16 weeks with Summer start dates.

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

Number of Places1 - 2
RequirementsRequired Skills:
  • 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. 
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

4. Deep Learning for Graphs
Project Background

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. 

Nature of Work
  • 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.
Duration of Internship

12 to 16 weeks with Summer start dates.

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

Number of Places1 - 2
RequirementsRequired Skills:
  • 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. 
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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

 

5. Applied Machine Learning
Project BackgroundOur Applied Machine Learning team works on innovative problems that require applying cutting-edge machine learning algorithms to cross-domain applications including material discovery, electronic design automation, operation planning and scheduling, etc.
Nature of Work
  • 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.
Duration of Internship

12 to 16 weeks with Summer start dates.

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

Number of Places1 - 2
RequirementsRequired Skills:
  • 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. 
AssessmentN/A
SalaryDependent on qualification of candidate
Application

Application Deadline: April 25, 2021 (Sunday)

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