Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.

Additional Responsibilities

Analyzing model behavior and optimizing models to achieve better accuracy, efficiency, and robustness in various applications.

Proposing and experimenting with innovative methods to enhance the multimodal capabilities of AI systems.

Collecting and curating multimodal datasets or benchmarks.

Conducting evaluations on multimodal capabilities.

Presenting findings at internal meetings and top-tier venues.

Required Qualifications

Currently enrolled in a master’s or PhD program in Computer Science or a related STEM field.

Other Requirements

Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.

In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.

Preferred Qualifications

Current knowledge of deep learning concepts.

Proficient analytical, problem-solving, and communication skills.

Experience publishing academic papers in the field of Artificial Intelligence.

Impact-driven mindset with the ability to work and learn in a collaborative and diverse environment.

Coding proficiency in deep learning frameworks and experience in training and evaluating deep learning models, e.g., large language models, multimodal models, diffusion models.