MIT Quantum Initiative launches postdoctoral fellowship program
The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.
The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.
The professor of physics and inaugural director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions will lead LNS and continue his research in particle physics.
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
“Scientific American” showcases the history and future of America’s scientific engine, highlighting promising young scientists and icons at MIT and beyond.
The fellowships in applied sciences, engineering, and mathematics recognize doctoral students who are pursuing solutions to the most pressing challenges in science and technology.