Research Intern - Artificial Intelligence

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, computer science, mathematics, economics, physics, healthcare, and the environment.

• Research and Analysis: Conduct thorough research on world modeling, propose new world modeling framework and further test its validity.
• Documentation and Reporting: Prepare detailed documentation of simulations, methodologies, and findings. Present results and insights to team members and stakeholders.
• Innovation and Problem-Solving: quickly identify the pros/cons of existing world modeling methods and propose novel approaches for world modeling.

• Currently enrolled in a Master or PhD program in Computer Science, Electrical Engineering, Mathematics or a related field.
• Ability to work independently and collaboratively in a dynamic and vibrant research environment.
• Willingness to embrace knowledge outside your field of research interest.
• Solid programming skill in Python, PyTorch and experience conducting experiments and writing papers.
• Familiarity with current various world modeling methods.
• Experience in LLM, either pre-train or post-train.
• Experience in RL, Computer Vision, Signal Processing is a plus.
• Relevant publications such as CVPR, ACL, ICML, ICCV, ECCV, NeurIPS, ICLR, EMNLP etc.

• Industry leading healthcare
• Educational resources
• Discounts on products and services
• Savings and investments
• Maternity and paternity leave
• Generous time away
• Giving programs
• Opportunities to network and connect

Microsoft Research provides a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, computer science, mathematics, economics, physics, healthcare, and the environment.