Research Intern - Machine Learning Optimization

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

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. Our researchers and engineers 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.

The Reinforcement Learning team at Microsoft Research, Redmond (https://aka.ms/rl_redmond) seeks exceptional interns in the areas of reinforcement learning, machine learning, artificial intelligence, robotics, decision-making and related fields.

The team is comprised of researchers, engineers, and postdocs who take a broad perspective on developing new reinforcement learning techniques that will power the next generation of intelligent systems.

We seek applicants from all areas of reinforcement learning, machine learning, artificial intelligence, robotics, decision-making and related fields with a passion and demonstrated ability for research.

Interns will work closely with research mentors on research projects with the goal of publishing results in top venues, as well as putting these ideas into practice.

During a 12-week internship, students are paired with mentors and expected to collaborate with other interns and researchers, present findings, and contribute to the vibrant life of the community. Internships are offered year-round, although they typically begin in the summer.

All internships are paid. We will help with visa applications where needed.

Examples of current projects and directions in reinforcement learning include:

• Theoretical Foundations of Reinforcement Learning: Exploration, learning from logged data, and imitation learning
• Generalization in Reinforcement Learning through learning transferable representations
• Reinforcement Learning applications in robotics, particularly synergistic with the topics mentioned above
• Reinforcement Learning in domains consisting of natural language interactions.

For a sampling of recent publications in reinforcement learning from our lab, please see https://aka.ms/rl_redmond. We also collaborate broadly with researchers in other groups and labs. For a broader overview of the entire Reinforcement Learning research community at MSR, please see https://www.microsoft.com/en-us/research/theme/reinforcement-learning-group/

You will need to submit your CV and the names of two references (including your graduate advisor)

Responsibilities

Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, interns learn, collaborate, and network for life. Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, students are paired with mentors and expected to collaborate with other 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.

Qualifications

In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position. 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.

Required Qualification

Accepted or currently enrolled in a PhD program in Computer Science or a related STEM field.

Preferred Qualification

Prior research experience in reinforcement learning or a related area.