Research Intern - Machine Learning

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, healthcare, economics, and the environment.

We are a team at Microsoft Research, Redmond focused on developing and applying advanced artificial intelligence (AI) models and algorithms to help solve complex scientific and engineering challenges across the atomistic, process, deployment scales. Our team is diverse, comprising of scientists with expertise across computer science, chemistry/biology, and engineering and is passionate about translating research into real-world impact. We are highly collaborative and draw expertise from teams across Microsoft Research and Azure.

Required Qualifications

• Currently enrolled in a PhD program in Computer Science (machine learning, deep learning) 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

• Experience in working on research problems related to 1 of the following:
  • Power distribution and grid modelling
  • Modeling and optimization of industrial processes
  • Generative design of 3D structures
  • Multi-agent modeling for decision making
  • or similar areas
• A proficient foundation in mathematics and physics, and background knowledge in related fields.
• Experience with deep generative modelling, and deep learning architectures.
• Skills in algorithmic problem-solving and software development (C++, Python, C#, etc.), proficient in using deep learning libraries such as PyTorch.
• Diligence, initiative, and excellent organizational and communication skills.
• Publications in top-tier conferences or journals in machine learning or related scientific fields.

The base pay range for this internship is USD $6,550 - $12,880 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,480 - $13,920 per month.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: 

Microsoft accepts applications and processes offers for these roles on an ongoing basis.

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.

Research Interns will participate in AI projects for process optimization, supply chain modeling, industrial engineering, design and implement advanced models and algorithms, and collaborate with researchers across geographies (if applicable). Research Interns will work with their mentor and group to address an industrial problem with machine learning (ML). Examples could be:

• Power distribution and grid modelling.
• Modeling and optimization of industrial processes.
• Generative design of 3D structures.
• Multi-agent modeling for decision making.