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Overview

Protecting U.S. residents and visitors is among our nation’s highest priorities. As adversaries gain access to sophisticated technologies and materials, the threats grow more dynamic and complex—from cyber and nuclear to chemical and biological weapons of mass effect and other forms of terrorism. The PNNL national security mission employs our researchers, tools, and technologies to play a key role in advancing the ability to identify and secure nuclear materials, detect weapons of mass effect, manage nonproliferation treaties, secure our nation's borders, and protect critical infrastructures. PNNL’s scientific discovery and capabilities—rooted in innovative theory, methods, algorithms, and tools—are enabling stronger, more resilient technologies and systems to safeguard national security. Coupled with decades of radiological and nuclear materials expertise, advanced computing and threat analysis capabilities, and a broad fundamental science base, we are identifying and countering emerging threats that have significant impact at home and around the globe.

The Applied AI Sytems (AAIS) Group within the National Security Directorate is looking for an early-career scientist with a background in mathematics, statistics, data science, and domain science to contribute a growing portfolio of projects addressing threats to the health of humans, animals, plants, and their surrounding environments.

Data scientists in the AAIS group use mathematics, statistics, and data analysis techniques to develop high quality and defensible methods and tools to address critical scientific challenges in national security, energy, environment, materials sciences, and fundamental sciences. In many cases, our research is deployed across a variety of computer architectures to support big data analytics problems. Examples of our capability areas include:

• Mathematics and Statistics: We rely on deep technical expertise in classical mathematics, statistics, and computational modeling to identify, develop, and defend algorithmic solutions to challenging scientific problems. This spans a wide variety of disciplines including experimental design, optimization, uncertainty quantification, signal processing, functional analysis, modeling, artificial intelligence, machine/deep learning, game theory, graph theory, and Bayesian modeling. We also have deep expertise in bringing the areas of topology, algebra, and geometry to bear on data science problems. Recognizing that no one tool or model can provide the whole solution, we work together to produce innovative solutions that go beyond what we can do ourselves.

• Domain Science Driven Solutions: We pride ourselves on choosing the right solution for the problem at hand. This is only possible through close partnerships with domain science experts including biologists, chemists, computer vision experts, geospatial analysts, nuclear chemists and engineers, material scientists, environmental scientists, and natural language processors. Our team understands that domain-specific characteristics should steer solutions—we guide experimental design and study planning, data collection, developing methods and executing analyses, reporting results and providing recommendations, and establishing data archival procedures. Our integral role in developing and executing study lifecycles results in explainable, reproducible, and validated research across the entire breadth of laboratory research including problems in critical-infrastructure analysis, classification of multi-omic functionality, environmental planning, nuclear safety, and national security.

• Uncertainty, Risk, and Tradeoffs Analysis: We develop and deploy operational decision-making tools in several domains using model-based and data-driven learning. In doing so, we characterize operations, risk, resilience, and deterrence; incorporate adversarial behavior; and optimize solutions under limited resource constraints. We consider real-world uncertainties around supply chains and concepts of operations, imperfect measurements and observations, human intervention, and external impacts. In the face of these challenges, we provide strategic options and alternatives, quantify confidence in our recommendations to manage risks, and provide effective and achievable solutions that support operational objectives.

• Deployment to Users: At our core, we are applied researchers and provide results and tools to stakeholders including data scientists, subject matter experts, decision, and policy makers. We serve diverse communities and work to communicate effectively by facilitating educational courses, producing high quality papers for peer reviewed publication, and creating user-friendly software tools that can be deployed in a variety of environments.

• Data science researchers and practitioners work side by side to apply advanced theories, methods, algorithms, models, evaluation tools and testbeds, and computational-based solutions to address complex scientific challenges affecting a wide range of domains and application areas. Core domain knowledge is beneficial, such as in the nuclear, biological, energy, materials, or chemical science spaces. 

The successful candidate will work in interdisciplinary teams to develop and address challenging problems as well as contribute to software solutions, new project ideas, written reports and publications, and technical presentations. Strong written and verbal communication skills and ability to work with a diverse team are desired.

Responsibilities

Designs, develops, and implements methods, processes, and systems to analyze diverse data. Applies knowledge of statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data. Produces solutions driven by exploratory data analysis from complex and high-dimensional datasets. Designs, develops, and evaluates predictive models and advanced algorithms that lead to optimal value extraction from the data. Demonstrates ability to transfer skills across application domains.

Expectations of our early-career data scientists include:

• Contribute professionally to a diverse team

• Build professional reputation for technical expertise

• Explore, manage, and experiment with data to answer research problems

• Applying and interpreting standard theories, principles, methods, and tools in statistics, such as experimental design, spatial statistics (e.g., kriging), and machine learning algorithms to national security applications

• Excellent verbal and written communication skills and the ability to work in a collaborative environment through written reports and slide presentations that communicate statistical approaches and findings to non-technical audiences

• Using high-level programming language programming, such as python

• Familiarity with existing deep learning libraries and machine learning packages

• Understanding of applying machine learning and artificial intelligence to domain specific applications, such as agricultural modeling, natural language processing, risk assessment, adversarial machine learning, social computing, computer vision, etc.

• Ability to contribute that knowledge to the academic and research strength of PNNL and have experience writing technical reports and demonstrating their insight and discovery.

• Ownership in professional goal setting and development

• Passionate and self-motivated with good time management skills

Qualifications

Minimum Qualifications:

• BS/BA or higher

Preferred Qualifications:

• A track record of working in Python

• Knowledge of common statistical methods, probability theory, and graduate-level linear algebra

• Experience with PyTorch, Tensorflow, or another auto-grad library, and the fundamentals of machine learning and deep learning

• Experience working in or familiarity with the One Health domain

• Active Federal Q Clearance or ability to maintain such clearance.

Hazardous Working Conditions/Environment

Not applicable.

Additional Information

This position requires the ability to obtain and maintain a federal security clearance.

Requirements:

• U.S. Citizenship

• Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.

• Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the candidate selected is subject to pre-employment and random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).

Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy until non-use of illegal drugs, including marijuana, for 12 months can be demonstrated.

Testing Designated Position

This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or 3-hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity

Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.

Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov .

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.

HSPD-12 PIV Credential Requirement

In accordance with Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, new employees are required to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

Mandatory Requirements

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Rockstar Rewards

Employees and their families are offered medical insurance, dental insurance, vision insurance, health savings account, flexible spending accounts, basic life insurance, disability insurance, employee assistance program, business travel insurance, tuition assistance, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company funded pension plan and may enroll in our 401k savings plan. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

• Research Associates excluded.

**Once eligibility requirements are met.

Click Here For Rockstar Rewards (https://careers.pnnl.gov/rockstar-rewards)

Notice to Applicants

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $86,900.00/Yr.

Maximum Salary

USD $138,800.00/Yr.