Applied Science: PhD Internship Opportunities - Multiple Locations

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.

As an intern at Microsoft, you’re stepping into a world of real impact from day one. You’ll collaborate with global teams on meaningful projects, explore cutting-edge technologies like AI, and kick start your career while doing it. With a strong focus on learning and development, this is your opportunity to grow your skills, build community, and shape your future—all while being supported every step of the way.

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.

Responsibilities

- 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.

- Prepare data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded and be able to describe actions taken to address data quality problems.

- Assist with the development of usable datasets for modeling purposes and support the scaling of feature ideation and data preparation.