Deep Learning and Inference Using Models with Low Precision Synapses and Binary Unit Activations
Office of the Director of National Intelligence (ODNI)
Reference Code
How to Apply

Create and release your Profile on Zintellect – Postdoctoral applicants must create an account and complete a profile in the on-line application system.  Please note: your resume/CV may not exceed 2 pages.

Complete your application – Enter the rest of the information required for the IC Postdoc Program Research Opportunity. The application itself contains detailed instructions for each one of these components: availability, citizenship, transcripts, dissertation abstract, publication and presentation plan, and information about your Research Advisor co-applicant.

Additional information about the IC Postdoctoral Research Fellowship Program is available on the program website located at:

If you have questions, send an email to  Please include the reference code for this opportunity in your email. 

Application Deadline
2/26/2021 6:00:00 PM Eastern Time Zone

Research Topic Description, including Problem Statement:

Deep learning has revolutionized the field of machine learning. However, current approaches to deep neural network training require backpropagation of errors with high precision. This poses a challenge for training deep neural networks on future generation, low-power edge computing platforms under the constraint of low-precision (possibly binary) weights and binary unit activations. Recent research on binary neural networks (BNNs) and spiking neural networks (SNNs) offers hope that a solution to this problem can be found. However, this remains an open problem. Approaches may involve simulators, field-programmable gate arrays (FPGAs), and/or neuromorphic hardware.

Example Approaches:

  • “EventProp: Backpropagation for Exact Gradients in Spiking Neural Networks” arXiv:2009.08378
  • “Training Binary Neural Networks with Real-to-Binary Convolutions” arXiv:2003.11535

Relevance to the Intelligence Community:

The Intelligence Community (IC) will increasingly rely on edge computing platforms to detect patterns of interest in sensor data. Developing algorithms for training and inference on future generation, low-power edge computing platforms will ensure that the IC is able to take full advantage of these platforms.

Key Words: Deep Learning, Machine Learning, Artificial Intelligence, Neuromorphic, Low Precision, Event Based Computing, Neural Networks, SNN, BNN


Postdoc Eligibility

  • U.S. citizens only
  • Ph.D. in a relevant field must be completed before beginning the appointment and within five years of the application deadline
  • Proposal must be associated with an accredited U.S. university, college, or U.S. government laboratory
  • Eligible candidates may only receive one award from the IC Postdoctoral Research Fellowship Program

Research Advisor Eligibility

  • Must be an employee of an accredited U.S. university, college or U.S. government laboratory
  • Are not required to be U.S. citizens
Eligibility Requirements
  • Citizenship: U.S. Citizen Only
  • Degree: Doctoral Degree.
  • Academic Level(s): Postdoctoral.
  • Discipline(s):
    • Chemistry and Materials Sciences (12 )
    • Communications and Graphics Design (2 )
    • Computer, Information, and Data Sciences (17 )
    • Earth and Geosciences (21 )
    • Engineering (27 )
    • Environmental and Marine Sciences (14 )
    • Life Health and Medical Sciences (45 )
    • Mathematics and Statistics (10 )
    • Other Non-Science & Engineering (2 )
    • Physics (16 )
    • Science & Engineering-related (1 )
    • Social and Behavioral Sciences (27 )

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