Postdoctoral Appointee - Neuromorphic Codesign; Onsite

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Sandia National Laboratories is the nation's premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting‑edge work in a broad array of areas. Some of the main reasons we love our jobs:

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• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work four ten‑hour days each week) compressed workweeks, part‑time work, and telecommuting (a mix of onsite work and working from home)
• Generous vacation, strong medical and other benefits, competitive 401(k), learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

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Are you passionate about working in collaboration with a highly interdisciplinary team of engineers, neuroscientists, computer scientists, and mathematicians? Our team is seeking an electrical engineering or computer engineering postdoctoral appointee to conduct research on deploying artificial intelligence and computational neuroscience algorithms onto neuromorphic computing hardware.

On any given day, you may be called on to:

• Co‑design novel brain‑inspired and machine learning algorithms and novel neuromorphic hardware. This includes analyzing, benchmarking, and modeling neuromorphic architectures.
• Find opportunities to improve future neuromorphic architectures targeting new application domains.
• Use neuromorphic sensors (such as event cameras) and neuromorphic processing to target edge computing applications like space and remote systems, autonomous vehicles, and cybersecurity.
• Publish research results in high‑quality journals and professional conference venues.

* Due to the nature of the work the selected applicant must be able to work onsite in Albuquerque, New Mexico. Relocation will be provided for those that qualify.

• Possess, or are pursuing, a PhD in electrical engineering, computer engineering, computer science, or related field;
  PhD must be conferred within five years prior to employment.
• Experience in developing and optimizing algorithms to specialized architectures such as neuromorphic hardware, FPGAs, GPUs, or machine learning accelerators.
• Experience in a common programming language such as Python, C++, or MATLAB.
• Able to acquire and maintain a DOE Q‑level security clearance.

• Interest in neural‑inspired and artificial intelligence algorithms (e.g., deep neural networks, spiking neural networks, recurrent neural networks).
• Interest in resource (e.g., SWaP or Data) constrained AI and deep learning methods and techniques. Experience with specialized computational architectures such as GPUs, FPGAs, neuromorphic processors, or machine learning accelerators.
• Experience with neural network modeling languages (PyTorch, Tensorflow, Keras, etc.) or neural modeling languages (e.g., PyNN, NEST, NEURON).
• Experience in algorithm‑hardware co‑design.
• Prior research activity, publications in computing or electrical engineering conferences is highly desirable (a list of publications should be included in your CV).

The Department of Cognitive & Emerging Computing (Org. 01421) pursues foundational research and development of:

• emerging general‑purpose energy‑efficient and beyond‑Moore computing paradigms;
• cognitive, brain‑inspired and neuromorphic computing, human‑machine interface technologies;
• advanced heterogeneous architectures based on integrated commodity components, special purpose accelerators, neural architectures and algorithms.

This posting will be open for application submissions for a minimum of seven (7) calendar days, including the posting date. Sandia reserves the right to extend the posting date at any time.

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