MIT's Laboratory for Nuclear Science is entering a new leadership phase with Professor Jesse Thaler named as its next director, effective Aug. 1. The appointment puts a prominent theoretical particle physicist at the head of a laboratory whose work now reaches across nuclear science, particle physics, cosmology, gravity, field theory, and quantum information science.
Thaler succeeds Professor Bolek Wyslouch, who directed LNS for the past decade. The transition also highlights a broader shift in fundamental physics: AI and machine learning are becoming central tools for managing complex data, building new algorithms, and supporting discovery.
A leadership change with a clear research signal
Thaler is the William and Emma Rogers Professor of Physics in the MIT Center for Theoretical Physics — a Leinweber Institute, or CTP-LI. His work combines quantum field theory and machine learning to address outstanding questions in fundamental physics.
That combination matters for LNS because the laboratory is not limited to one narrow branch of physics. Established in 1946 to support nuclear and particle physics, LNS now includes research areas that span some of the most abstract and data-intensive problems in science.
Nergis Mavalvala, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics, pointed to Thaler's research record as part of the reason the appointment fits this moment. She said his work includes pioneering contributions on particle jets at the Large Hadronic Collider and leadership in combining AI and machine learning with fundamental particle physics.
The emphasis is not only on one scientist's field. It is also on how modern physics is increasingly organized around collaborations that cross older boundaries between theory, computation, experiments, and data science.
Why AI is central to the next phase
Thaler's background makes the AI connection especially prominent. Since 2020, he has served as the inaugural director of the National Science Foundation AI Institute for Artificial Intelligence and Fundamental Interactions, or IAIFI. That institute was recently renewed for another five years.
Mike Williams, professor of physics, will succeed Thaler as IAIFI director. The leadership handoff means Thaler will move from directing an institute focused specifically on AI and fundamental interactions into a broader role at LNS, while the AI-focused institute continues under new leadership.
Thaler has described AI as a practical response to the scale and complexity of current research. In particle physics, he noted, researchers are developing algorithms to handle the data deluge from collider experiments and to perform difficult theoretical calculations. The point is not simply to make existing work faster. According to Thaler, this work has direct implications for discovering new physics, while the algorithms can also be valuable beyond the field.
LNS is also positioned to pursue new research projects through the Department of Energy's Genesis Mission, which focuses on AI-enabled scientific discovery. Within the facts provided by MIT, that places the laboratory at the intersection of existing physics expertise and new AI-driven capabilities.
From IAIFI to LNS
At IAIFI, Thaler has supported education and research at the intersection of physics and AI. The institute's leadership, working with the MIT Institute for Data, Systems, and Society, created a doctoral program in physics, statistics, and data science.
IAIFI also created dedicated postdoctoral fellowships. The purpose of those fellowships, as described in the source material, is to give early-career researchers freedom to pursue interdisciplinary work.
Those details suggest the kind of framework Thaler hopes to bring to LNS. He has said that giving young scientists room to build connections across domains, universities, and career stages has been transformative within IAIFI. Bringing that approach into LNS could shape how the laboratory organizes research across its wide scientific range.
The appointment therefore has two layers. On one level, it is a change in laboratory leadership. On another, it is a sign that AI, data science, and cross-disciplinary training are becoming part of the operating model for major fundamental physics programs.
A broader MIT physics role
As director of LNS, Thaler will also oversee his home center, CTP-LI. That role is notable because the center last year received a donation from the Leinweber Foundation to establish a network of theoretical physics research institutes.
According to the Science Philanthropy Alliance, a nonprofit organization that promotes philanthropy for science, this constitutes the largest philanthropic commitment ever for this field. The source does not provide further details here, but the connection places Thaler's new LNS role alongside a major development for theoretical physics research and education at MIT.
Thaler's academic path also reflects a long connection to fundamental physics research. He received his PhD in physics from Harvard University in 2006 and his BS in math/physics from Brown University in 2002. From 2006 to 2009, he was a fellow at the Miller Institute for Basic Research in Science at the University of California at Berkeley. He joined the MIT faculty in 2010.
What the appointment means for the laboratory
The clearest implication is that LNS will be led by someone whose work sits directly at the meeting point of theoretical particle physics, AI, and machine learning. That matters because the laboratory's research portfolio now extends beyond its original nuclear and particle physics foundation into fields where computation, data, and theory are closely intertwined.
For researchers inside LNS, the appointment points toward more attention on AI-driven capabilities, interdisciplinary programs, and pathways for young scientists to work across domains. For the wider physics community, it reinforces a broader trend already visible in the source material: fundamental discovery increasingly depends on both deep physics knowledge and advanced computational methods.