Applied Science: PhD Internship Opportunities - Vancouver, BC, Canada

Come build community, explore your passions and do your best work at Microsoft with thousands of university interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead.

As an Applied Science PhD Intern at Microsoft, you will be at the forefront of technological innovation, working collaboratively to bring research to life in our products and services. You'll gain expertise in cutting-edge research areas, apply advanced concepts to real-world needs, and use state-of-the-art tools to make a tangible impact on product quality and business outcomes. You'll contribute to the creation of intelligent solutions through data analysis, modeling, machine learning, and/or AI, LLM, SLM and agent, ensuring our products remain at the leading edge of innovation.

We are looking for interns with diverse research backgrounds to join Microsoft Turing team and work on applied research problems. At Microsoft Turing, we do cutting-edge AI research that directly powers M365 Copilot. We’re advancing applied AI to shape the next generation of Microsoft 365 Copilot - from post-training LLMs to computer-using agents and reasoning models.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate and empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Please note this application is only for internships based in our Vancouver, British Columbia, Canada office. For internships in other offices, please see our Careers site.

• Analyze and improve performance of advanced algorithms on large-scale datasets and cutting-edge research in machine intelligence and machine learning applications.

• Think through the product scenarios and goals, identify key challenges, then fit the scenario asks into Machine Learning (ML) tasks, design experimental process for iteration and optimization.

• Implement prototypes of scalable systems in AI applications.
  Gain an understanding of a broad area of research and applicable research techniques, as well as a basic knowledge of industry trends and share your knowledge with immediate team members.

• Leverage interdisciplinary expertise and knowledge across NLP, LLM, computer vision, and other related domains to accelerate innovation in artificial intelligence.

• Disseminate research findings through publications in peer-reviewed journals, top-tier conferences, and other relevant venues, and present results both internally and externally.