Description:   

We are seeking interns with solid Computer Science, Machine Learning, Statistics, and Mathematics backgrounds who would be interested in exploring research directions in one of the following general domains:

(i) Large Language Models (LLMs) and Natural Language Processing (NLP)

(ii) Machine Learning (ML) Foundations—including in Architecture, Optimization, Graph Neural Networks (GNN), Multi-Modal Learning (MML), etc.

(iii) Reinforcement Learning (RL) 

(iv) Automatic Design Space Exploration (DSE)

(v) Theoretical and/or Empirical Investigation of Statistical Learning Techniques

Responsibilities and opportunities to learn:

• Work with the machine learning (ML) team within our IC-Lab to investigate, explore, develop and publish research results in machine and statistical learning in one of our focused or neighboring areas
• Investigate and explore cutting edge problems in domains such as long sequence processing and NLP, automatic design space exploration, reinforcement learning, computer vision, and multi-modal representation learning. 
• Help advance the theory and practice of machine and statistical learning and application through innovative research.

• Publish results in top machine learning conferences and/or journals.

   

Prefer candidates with some of the following qualifications—as related to general domains of focus mentioned above:

• Knowledge of (deep) reinforcement learning, optimization, and search techniques.
• Knowledge of statistical learning—e.g., deep neural networks, sequence processing, graph neural networks, etc. 
• Familiarity with ML life cycle, architectures, and model designs.
• Familiarity with ML implementation environments and platforms such as PyTorch and/or Tensorflow.
• Familiarity with distributed system processing, Linux and Python environments, source code management, and team development practices.
• Familiarity with large language models (LLMs) and Visual Language Models (VLMs) is a plus.

Key qualifications:

• Well-organized, detail-oriented, passionate about learning, motivated, and team player.
• Verbal and written communication skills.
• Ph.D. student in Computer Science, Machine/Statistical Learning, Computer Engineering, or closely related majors.