Postdoctoral Appointee: Neural Networks, Onsite

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.

About the role

We are seeking motivated postdoctoral candidates to advance the theory of brain-inspired algorithms and apply them to complex, real-world problems. The successful candidate will join an interdisciplinary team of computer scientists, mathematicians, engineers, and neuroscientists pursuing advanced research and development in neuromorphic computing, artificial intelligence, and spiking neural networks across a range of applications.

• Develop and extend neural-inspired artificial intelligence algorithms;
• Research theoretical principles and foundations necessary for model interpretability and introspection;
• Program and test algorithms on neuromorphic and AI accelerator hardware;
• Apply existing state-of-the-art methods and algorithms to domain data;
• Engage with the community for conferences, workshops, proposals, and outreach;
• Develop and support open-source research software packages;
• Publish research results in high-quality journals and competitive conference venues.

Due to the nature of the work, the selected applicant will be required to work onsite. Relocation provided for those who qualify.

Requirements

• PhD in computer science, mathematics, theoretical neuroscience, physics, or a relevant field conferred within 5 years prior to start date.
• Experience with theoretical or practical aspects of either neuromorphic algorithms or artificial intelligence.
• Experience in a common programming language such as Python or C++.
• Ability to obtain and maintain a DOE Q clearance.

Qualifications We Desire

• Interest in developing neural-inspired and cutting-edge artificial intelligence algorithms (e.g., spiking neural networks, Bayesian neural networks, RNNs, LLMs) or in the deployment of such algorithms.
• 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.
• Prior peer-reviewed research publications.
• Demonstrated ability to work with others and contributed in a team environment.
• Desire to work as part of a collaborative, multi-disciplinary team.
• Willingness to be flexible in assignments and develop expertise in different areas of neuromorphic computing.

About Our Team

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 heterogenous architectures based on integrated commodity components, special purpose accelerators, neural architectures and algorithms.

Benefits

• Challenging work with impact contributing to security, peace, and freedom worldwide
• Extraordinary co-workers
• Some of the best tools, equipment, and research facilities in the world
• Career advancement and enrichment opportunities
• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 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 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

*These benefits vary by job classification.

Schedule

This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance.

The PhD must have been conferred within five years prior to employment.