Flatiron Research Fellow, NeuroAI and Geometric Data Analysis

Description

Applications are invited for Flatiron Research Fellowships (FRF) in the NeuroAI and Geometric Data Analysis Group (SueYeon Chung, PI) at the Center for Computational Neuroscience at the Flatiron Institute of the Simons Foundation, whose focus is on understanding computation in the brain and artificial neural networks by: (1) analyzing geometries underlying neural or feature representations, embedding and transferring information, and (2) developing neural network models and learning rules guided by neuroscience. To do this, the group utilizes analytical methods from statistical physics, machine learning theory, and high-dimensional statistics and geometry.The CCN FRF program offers the opportunity for postdoctoral research in areas that have strong synergy with one or more of the existing research groups at CCN or other centers at the Flatiron Institute. In addition to carrying out an independent research program, Flatiron Research Fellows are expected to: disseminate their results through scientific presentations, publications, and software release, collaborate with other members of the CCN or Flatiron Institute, and participate in the scientific life of the CCN and Flatiron Institute by attending seminars, colloquia, and group meetings. Flatiron Research Fellows may have the opportunity to organize workshops and to mentor graduate and undergraduate students.

 

The mission of CCN is to develop theories, models, and computational methods that deepen our knowledge of brain function — both in health and in disease. CCN takes a “systems" neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning.  CCN’s current research groups include computational vision (Eero Simoncelli, PI), neural circuits and algorithms (Dmitri ‘Mitya’ Chklovskii, PI), neuroAI and geometric data analysis (SueYeon Chung, PI), and statistical analysis of neural data (Alex Williams, PI), and is planning to expand the number of research groups in the near term. Interested candidates should review the CCN public website for specific information on CCN’s research areas.  Applicants who are interested in a joint appointment between two CCN research groups should submit the same application to both groups, noting the dual application in their research statement.  Please note that Alex William’s statistical analysis of neural data group is not recruiting at CCN in 2023.

 

FRF positions are two-year appointments and are generally renewed for a third year, contingent on performance. FRF receive a research budget and have access to the Flatiron Institute’s powerful scientific computing resources. FRF may be eligible for subsidized housing within walking distance of the CCN. 

 

Review of applications for positions starting between July and October 2024 will begin in November 2023.

 

For more information about life at the Flatiron Institute, visit https://www.simonsfoundation.org/flatiron/careers.

Qualifications

MINIMUM QUALIFICATIONS

Education

• PhD in computational neuroscience or a relevant technical field such as electrical engineering, machine learning, statistics, physics, or applied math.

 

Related Skills & Other Requirements

• Flexible multi-disciplinary mindset;

• Strong interest and experience in the scientific study of the brain;

• Demonstrated abilities in analysis, software and algorithm development, modeling and/or scientific simulation;

• Ability to do original and out