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Sandia National Laboratories · 13 hours ago

Postdoctoral Appointee - Computational Neuroscience (Onsite)

Albuquerque, NM

Full-time

Onsite

Senior Level

Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation. They are seeking a computational neuroscience postdoctoral appointee to conduct research at the interface of neuroscience, artificial intelligence, and implementing neural-inspired algorithms on hardware.

GovernmentInformation TechnologyNational Security

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Draw inspiration from neuroscience to develop novel algorithms to tackle real-world problems

Develop neurobiological models at differing levels of biological complexity, ranging from neural network theory to neural circuit models constrained by current understanding of biophysical mechanisms underlying sensory processing and learning

Work with computer scientists, mathematicians, and engineers to abstract neural computations such as dendritic computation, short-term plasticity, and microcircuit computations for incorporation into artificial intelligence algorithms and human-made computing systems

Develop techniques for mapping novel brain-inspired and AI models onto existing and emerging neuromorphic hardware. This includes analyzing, benchmarking, and modeling neuromorphic architectures

Publish research results in journals and professional conference venues

Qualification

Computational NeuroscienceNeural AlgorithmsArtificial Intelligence ModelsNeuromorphic HardwarePythonC++Neural Network ModelingResearch PublicationCollaboration

Required

Possess, or are pursuing, a PhD in theoretical neuroscience, computer science, mathematics, physics or a relevant field; PhD must be conferred within five years prior to employment

Experience with theoretical or practical aspects of either neural algorithms, artificial intelligence models, or neuromorphic hardware

Experience in a common programming language such as Python or C++

Able to obtain and maintain a DoE Q clearance

Preferred

Interest in developing neural-inspired (e.g., spiking neural network, population codes) and cutting-edge artificial intelligence algorithms (e.g. transformer models, RNNs, diffusion models) or in the deployment and application of such algorithms

Experience with specialized computational architectures such as GPUs, FPGAs, neuromorphic processors

Experience with neural network modeling languages (PyTorch, Tensorflow, Keras, etc) or neural modeling languages (Brian, NEST, etc)

Prior peer-reviewed publications in top-tier journals are highly desirable

Desire to work as part of a collaborative, multi-disciplinary team