Job Description

What Your Job Will Be Like:

We are seeking highly motivated postdoctoral candidates to explore, study and develop machine learning or neuromorphic methods for solving real-world problems. In the Cognitive and Emerging Computing department, we perform high-level R&D in machine learning and spiking neural network solutions for a variety of application domains from across the larger laboratories complex. Working from Fundamental Theory through to Practical Machine Learning we work to increase capability, understanding and efficiency in domains such as space remote sensing, high energy physics, scientific computing and natural language/document processing.The successful candidate will join our fun and interdisciplinary team of computer scientists, mathematicians, engineers and neuroscientists and will work closely alongside an assigned mentor. Sandia has opportunities for internal career advancement and to learn from and collaborate with a large number of scientists and engineers.

A strong basis in one of Fundamental Theory (mathematics, statistics, computer science), Practical Machine Learning (Convolutional Neural Networks, Attention-based Methods, Language Models) or Relevant Applications (Space Remote Sensing, High Energy Physics, Scientific Computing, Natural Language/Document Processing) is a necessity.

We work on a varied set of problems. Example responsibilities could include:

• Develop and extend machine learning or neuromorphic algorithms

• Publish research results in high-quality journals and competitive conference venues

• Program and test algorithms on neuromorphic and AI accelerator hardware

• Apply existing innovative methods to domain data

• Explore deployment characteristic using both Sandia-developed and open-sourced tools

• Research theoretical principles and model interpretability/model introspection

• Develop software demonstrations of recent results/methods

• Engage with the community for conferences, workshops, proposals and outreach

• Develop and support open-source research software packages

Qualifications We Require:

• PhD in Computer Science, Mathematics, Statistics, Physics, Computer Engineering or a relevant field conferred within five years prior to employment

• Experience with theoretical or practical aspects of machine learning, especially neural networks or similar techniques

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

• Able to acquire and maintain a DOE Q-level security clearance

Qualifications We Desire:

• Interest in developing neural-inspired and cutting-edge machine learning algorithms (e.g. deep/convolutional neural networks, spiking neural networks, recurrent neural networks) or in the deployment and application 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 research peer-reviewed publications are highly desirable

• Desire to work as part of a collaborative and diverse team

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