Vacancy expired!
Company Description
Join us and make YOUR mark on the World!Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory's mission. Job Description We have an opening for an experienced Cybersecurity Data Scientist with a background in machine learning for cybersecurity applications. You will provide subject matter expertise and leadership to research projects in cybersecurity for critical infrastructure systems and civilian networks. You will participate in strategy and business development for the Cyber and Infrastructure Resilience (CIR) program. This position is programmatically in Global Security's E Program and administratively will report to the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate.This position will be filled at eitherlevel based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.In this role you will- Lead and support a diverse range of advanced research projects requiring in-depth analysis and creative use of innovative methods in machine learning and data analytics for cyber threat detection in operational technology (OT) environments, partnering with senior management and organizations across the Laboratory.
- Ensure growth of existing and development of new machine learning and data analytics capabilities at LLNL.
- Provide subject matter expertise to inform the development of new algorithms, while identifying data sets that can be used for cyber threat detection in OT environments.
- Identify new opportunities and applications of LLNL's data analytics capabilities and help create vision and technical direction for existing work in the area under the consultative direction of leadership.
- Develop new program growth opportunities through interaction with existing and potential sponsors with the development of research proposals.
- Identify, define, and determine scope of highly complex data analytics problems in the cybersecurity domain.
- Develop cross-domain strategies for increased network security and resiliency of critical infrastructure, partnering with researchers in other disciplines.
- Perform other duties as assigned.
- Guide and provide scientific and technical direction for a portfolio of highly complex technical tasks and projects that consistently require the application of creativity and innovation, while setting broad research/project visions, and strategizing and influencing the technical direction for the Laboratory and sponsors, wielding extensive influence with senior management and policy makers.
- Provide highly innovative solutions to abstract complex problems/ideas, convert them into useable algorithms/software modules, and provide solutions that require in-depth analysis of multiple factors and the creative use of established methods.
- Lead high-level goal setting and strategic planning, while directing and accomplishing project/program goals and objectives that significantly impact major Laboratory programs and contribute to the revolutionary advancement of knowledge.
- Master's degree in Computer Science, Computer Engineering, or related field or the equivalent combination of education and significant related experience.
- Expert level experience in Python, C, or C.
- Substantial experience implementing a deep learning workflow using one or more of the following frameworks: Theano, TensorFlow, PyTorch, or Keras.
- Subject matter expertise applying algorithms in one or more of the following Machine Learning areas: deep learning, unsupervised feature learning, ensemble methods, and/or probabilistic graphical models.
- Highly advanced knowledge of network protocols, such as: DNS, HTTPS.
- Expert level knowledge of and/or substantial experience with computer vulnerabilities, such as, buffer overflows, code injection, format string, etc.
- Advanced ability to effectively lead teams, create technical direction and vision, write research proposals, and secure sponsor funding.
- Expert ability to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-cyber experts with the proficient interpersonal skills necessary to effectively collaborate in a team environment.
- Expert level knowledge of state-of-the-art technologies in machine learning and deep learning algorithms.
- Extensive experience planning the integration and implementation of new programs and/or operational best practices.
- Extensive project leadership experience with the ability to apply, lead and develop cutting-edge principles and research, while working independently and effectively managing concurrent technical tasks with competing priorities.
- PhD in Computer Science, Computer Engineering, or related field.
- Experience in systems engineering, including practical experience in critical infrastructure cybersecurity including knowledge of one or more of the following computer science disciplines: embedded systems, systems programming, software engineering, parallel programming and high performance computing, and significant experience with full-stack software development.
- Ability to secure sponsor funding through winning proposals and sponsor relationships with previous experience working for or with the Department of Energy, Department of Homeland Security, Department of Defense, or a utility company.
- Included in 2020 Best Places to Work by Glassdoor!
- Work for a premier innovative national Laboratory
- Comprehensive Benefits Package
- Flexible schedules (depending on project needs)
- Collaborative, creative, inclusive, and fun team environment
Vacancy expired!