We use cookies. Find out more about it here. By continuing to browse this site you are agreeing to our use of cookies.
#alert
Back to search results

Research Intern - Machine Learning and Optimization - Redmond

Microsoft
United States, Washington, Redmond
Nov 28, 2024
OverviewResearch 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.The Machine Learning and Optimization (MLO) group in MSR-Redmond performs research in the intersection of optimization, machine learning and systems. Example efforts include algorithms for cloud supply chain management and combining large language model (LLM) technology with optimization for efficient decision making. Our research leverages theoretical insights for designing algorithms and ML-based solutions that run efficiently at scale.
ResponsibilitiesResearch 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 are expected to design algorithms and prototype them, conduct experiments, and analyze results. They are encouraged to show initiative throughout the internship and suggest further directions for research. They are expected to document their ideas, and given suitable results, contribute to a paper.
Applied = 0

(web-5584d87848-llzd8)