Deep Learning Application Research

This is a part-time remote position supporting Peraton's NSWC Carderock customer. Periodic travel to NSWC Carderock in West Bethesda, MD will be required.

Peraton is hiring a part-time mathematician who will do the following:

Develop a new generation of scalable solvers for differential equations by applying Deep Learning (DL) to the associated Stochastic Differential Equations (SDE).
• This effort follows recent work demonstrating that a hybrid DL/SDE approach may lead to an efficient and scalable numerical model for the Poisson equation.
• The successful applicant will explore the potential expansion of this new approach to create new solvers for Navy applications that require less computational resources compared to classical finite element and finite difference methods.

Education and Experience:

Minimum of 7 years with Ph.D.

• Demonstrated knowledge (preferably published) of recent advances in Deep Learning techniques along with the mathematical theory of Stochastic Differential Equations.
• Coding experience using modern Deep Learning libraries.
• Ability to obtain an Interim DoD SECRET Clearance.
• US Citizenship.
• Periodic travel to NSWC Carderock in West Bethesda, MD

Desired:

• Active DoD Secret Clearance

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