School of Science
School of Science

Estimating suicide risk from text

A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.

Poitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders research

Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.

MIT Quantum Initiative launches postdoctoral fellowship program

The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.

Looking beyond natural sequences

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.

AI helps design new materials that work in the real world

The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.

Paving the way for greener ammonia production

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.

Alexander Rakhlin named director of the MIT Statistics and Data Science Center

An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.

MIT projects selected for funding under US Department of Energy’s Genesis Mission

Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.

Jesse Thaler named director of the Laboratory for Nuclear Science

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.

Toward a future that preserves benefits of neurotechnology for all

PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.