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R&D Associate Machine Learning Research Scientist

Date: Sep 10, 2021

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 6204 

Purpose

The Cyber Resilience and Intelligence Division in the National Security Sciences Directorate of Oak Ridge National Laboratory invites applications to the position of Machine Learning Research Scientist.

 

The Augmented Analyst Intelligence (A2I) group at ORNL performs research and development of tools and methods to augment an analyst’s accuracy, effectiveness, speed, confidence, and ability to process large amounts of multi-modal data. We work closely with domain experts in a variety of domains, including cyber security and intelligence analysis. A2I's activities involve first-class interdisciplinary research with other research groups at ORNL, collaborations with private industry and academic partners across the nation, and mission-specific support for national security sponsors. Our staff includes software engineers, mathematicians, researchers in machine learning, and UX developers. We publish papers on our applied research projects, but always with an eye on improving the national security of the nation by deploying new solutions.

A2I staff thrive in a culture of respect, diversity, curiosity, and discovery.

 

Responsibilities

Successful candidates will work in a collaborative R&D environment focusing on designing and implementing data analytics applications in applications of national security. The position requires innovative thinking to design and implement machine learning, statistical, probabilistic, or algorithmic solutions to real world problems in the national security space.

 

Successful candidates will have the opportunity to help write peer-reviewed papers, technical reports, and proposals for internal and external sponsors. They will also have the opportunity to contribute to open-source projects and create new open-source projects. Successful candidates will also often be part of a team that sees their software deployed to sponsor agencies.

 

Required Qualifications

  • The position requires a Ph.D. or M.S. (M.S. graduates require at least 2 years of experience) in Computer Science, Mathematics, or a related field.
  • Applied experience in at least one machine learning discipline such as natural language processing, anomaly detection, or related areas.
  • Excellent programming skills (Python or Golang preferred).
  • Foundational understanding of supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with large, multimodal datasets.
  • Experience working on Linux/Unix platforms.
  • Excellent communication skills for conveying technical material to both scientists and non-scientists in both written and oral presentations.
  • Self-disciplined work ethic and eagerness to tackle challenging research problems.
  • This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.

 

Preferred Qualifications

  • Candidates who have contributed to open-source projects are preferred.
  • Experience developing and deploying scalable machine learning models is preferred.

 

Our commitment to diversity:  As we strive to become the world’s premier research institution in the sciences and technologies that underpin critical national security missions, we are committed to creating an inclusive environment that highly values a diverse workforce.  We recognize that a breadth of perspectives, insights, and experiences are necessary to drive the level of innovation and discovery that is mission critical to national security sciences.  Our commitment extends beyond our workforce to the next generation of researchers with STEM education outreach that seeks to engage a diverse range of students.

 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.


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