Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here! The Machine Learning Department (MLD) at Carnegie Mellon University is a leading hub for research and education in artificial intelligence and machine learning. It focuses on developing innovative algorithms and models to address complex problems in diverse fields such as robotics, healthcare, and finance. The department offers a range of undergraduate and graduate programs, fostering a collaborative environment that bridges theoretical research and practical applications. Faculty and students frequently collaborate with industry and other academic disciplines to push the boundaries of what is possible with machine learning. MLD is seeking a Research Associate to carry out advanced directed research to help scientific processes maintain rigor. This position will require an in-depth knowledge of machine learning and statistics. The work will involve developing and implementing complex plans, conducting studies to understand efficacy and tradeoffs of these plans, and writing reports containing analytical descriptions of the plans and findings. Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Job Type
Full-time
Career Level
Entry Level
Number of Employees
501-1,000 employees