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Los Alamos National Laboratory · 2 weeks ago

Sparse Neural Network Design Post-Doctoral Research Associate(s)

Los Alamos, NM

Full-time

Onsite

New Grad, Entry Level

Los Alamos National Laboratory is a multidisciplinary research institution engaged in strategic science on behalf of national security. They are seeking highly motivated postdoctoral researchers to drive the research and development of novel sparse neural networks, including custom network design and computational experiments.

Security

Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Hand write custom sparse neural networks from scratch and perform computational experiments designed by mathematicians on the team

Interface with mathematicians and applied computer scientists to demonstrate the viability of novel neural network on challenging benchmark datasets/problems, using cutting-edge high-performance computing platforms

Have opportunities to publish in leading peer-reviewed journals and present research at conferences, and to visit academic collaborators at CU Boulder and Boston University

Qualification

Sparse neural networksScientific programmingMachine learningPythonC/C++Team software developmentOpen source contributionsMathematical codingCommunication skills

Required

A Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field, earned within the last 5 years

Demonstrated research excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures

Proficiency in scientific programming, preferably in Python or C/C++

Strong communication skills, both written and oral, demonstrated through publications and the cover letter

Preferred

Familiar with mathematical and coding aspects of neural networks

Contributions to prominent open source machine learning software projects, experience performing code reviews, and experience working in a team software development setting

Evidence of competitive excellence in machine learning (i.e., Kaggle competition rankings) and/or mathematics