BCS Fellows in Computation
Computational and theoretical approaches to understand brain and behavior
The BCS Fellows in Computation program in the Department of Brain and Cognitive Sciences provides highly creative scientists the opportunity to think and work independently as an alternative to traditional postdoctoral training. The program recognizes and supports young scientists during their most creative years, playing a role in their growth as they mature into leaders in the field.
BCS Fellows in Computation
Computational and theoretical approaches are fundamental to the progress of neuroscience and cognitive science. The goal of the BCS Fellows in Computation is to foster this progress and develop leaders in the field. Fellows are independent researchers with the ability to develop their own research programs and lead cross-PI collaborations. Fellows will have minimal formal responsibilities and constraints so they can devote their time to advancing our understanding of the brain and mind via computation as well as building collaborative efforts across BCS and MIT. Fellows participate in the rich interdisciplinary environment within BCS and across departments at MIT. The selected scholars receive two-year fellowships, with a possibility of extension to a third year, as well as a research allowance and access to high-performance computing resources. Salaries and benefits are competitive.
Fellows will be provided with resources to carry out research in computation, including access to high-performance computing clusters. Opportunities will exist for fellows to gain teaching experience if they desire, but there is no requirement that they will teach.
Fellows will be provided with robust resources for two years and an optional third year:
2021 BCS Fellows in Computation
Noga collaborates with several labs including the Computational Psycholinguistics Lab, EvLab, TedLab, and the Computational Cognitive Science Group. Her research aims to understand language and cognition from first principles, building on ideas and methods from machine learning and information theory.
Brian holds a PhD from University of California Berkeley and is also a postdoctoral fellow at the Redwood Center for Theoretical Neuroscience at Berkeley. As a BCS Computational Fellow in CSAIL, studies emergent properties in learning algorithms and unsupervised learning models.
BCS typically selects one to two scholars who exhibit exceptional promise and drive to join the program. To be eligible, a candidate will have recently received a PhD (within one year) or be about to receive a PhD in a computationally-focused field (e.g. Neuroscience, Math, Computer Science, Engineering, Physics) by the start of the Fellowship term. Candidates must be nominated for Fellowships, usually by their research advisors or other distinguished scientists who are familiar with their work. A letter of nomination should include an assessment of the candidate's work and talents, the candidate's CV, as well as the names and email addresses of the candidate and two additional people who have agreed to write letters of recommendation.
Send nomination letters to:
HR Administrator, Department of Brain and Cognitive Sciences
77 Massachusetts Ave., 46-2005
Cambridge, MA 02139