Pacific Northwest National Laboratory

Role Description Pacific Northwest National Laboratory’s Nuclear Sciences Division is seeking a Strategic Program Advisor to be responsible for the management of PNNL’s portfolio of microreactor and advanced reactor related projects. This person would be responsible for understanding national trends, regulations, policies, and technical issues related to microreactor and advanced reactor siting, licensing, transportation, used nuclear fuel management, and decommissioning. The Strategic Program Advisor will work with senior leaders from across the organization to deliver successful outcomes tailored to PNNL and sponsor needs. - Work with senior PNNL leaders to develop programmatic strategies, using existing PNNL capabilities and partnerships with other national laboratories and industry, to meet Department of War (DoW), Department of Energy (DOE), Nuclear Regulatory Commission (NRC), and National Nuclear Security Administration (NNSA) objectives related to the development of microreactors and advanced reactors. - Support PNNL’s work with DoW/OECIF in advancing the development, siting, deployment, redeployment, and decommissioning of microreactors and advanced reactors. - Support PNNL’s work with the Army in the development of regulations and policy for microreactors on DoW installations. - Support the DOE NE Microreactor Program (MRP) National Technical Director (NTD) in the management of the DOE NE Microreactor Program including leading and developing all internal and external reporting of performance while collaborating activities integrated across multiple synergistic DOE Laboratory projects, with Microreactor Applications Research Validation and Evaluation (MARVEL) project including but not limited to MRP, TREAT, and MFC. - Support the MRP NTD and Microreactor Applications Research Validation and Evaluation (MARVEL) MARVEL technical lead with technical comprehension of engineering, procurement, quality, and industry processes including their interfaces and interdependencies while managing project management teams. - Enhance future demonstration planning with coordination between MARVEL technical lead, other laboratories, industry partners, government agencies, and independent sponsors. - Create and implement strategies coordinated with sector and division plans that will enable PNNL to deliver cutting-edge solutions to DoW, DOE, NNSA, and NRC objectives in partnership with industry and other national laboratories focused in the areas of microreactor and advanced reactor development, siting, deployment, redeployment, and decommissioning. - Develop and grow relationships with other DOE labs, research institutions, and industry to collaborate on large-scale projects of national importance. - Identify, attract, mentor and guide junior to senior level staff to develop their technical and strategic leadership competencies. Qualifications - Minimum Qualifications: - BS/BA and 13 years of relevant experience -OR- - MS/MA or higher and 11 years of relevant experience - Preferred Qualifications: - Strong understanding of microreactor and advanced reactor national and international policies and regulatory frameworks. - Demonstrated program and project leadership experience in the areas of microreactor and advanced reactor development, siting, deployment, and management. - Demonstrated experience working with DoW, DOE, DHS, and private industry. - Proven ability to create and execute national level strategy, identify and interact with key stakeholders, prepare program proposals, and generate future R&D or mission application directions. - Excellent interpersonal, written and oral skills; the ability to effectively lead interdisciplinary teams, and a strong orientation toward advancing state-of-the-art technical capabilities. - Ability to obtain a 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 applicant selected for hire is subject to pre-employment drug testing, and post-employment 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). - 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. Benefits - Medical insurance - Dental insurance - Vision insurance - Robust telehealth care options - Several mental health benefits - Free wellness coaching - Health savings account - Flexible spending accounts - Basic life insurance - Disability insurance* - Employee assistance program - Business travel insurance - Tuition assistance - Relocation - Backup childcare - Legal benefits - Supplemental parental bonding leave - Surrogacy and adoption assistance - Fertility support - Employees are automatically enrolled in our company-funded pension plan* and may enroll in our 401 (k) savings plan with company match* - Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

Role Description At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. The Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing: - Artificial intelligence - Applied mathematics - Computing technologies - Data and computational engineering Responsibilities include: - Realizing the potential for science to leverage on-demand cloud scaling and resource diversity. - Controlling and managing costs related to job orchestration. - Requesting SLO constraints with respect to a job’s cost. - Scheduling task parallelism, managing data objects, selecting compute instances, and assigning storage resources. - Tracking costs and ensuring they stay within budgets. Relevant research topics include: - Developing job resource telemetry, cost introspection, modeling, and prediction. - Cross-platform job control mechanisms for alerts, checkpointing, and hard stops. - Optimized job execution policies adapted to cost profiles. The successful applicant will work within the Future Computing Technologies group and have demonstrated expertise in a topic closely related to performance modeling and scientific workloads. The researcher should be creative, self-motivated, and ready to publish at top-tier venues. Qualifications - Currently enrolled/matriculated in a PhD program at an accredited college. - Minimum GPA of 3.0 is required. - Pursuing a degree in computer science, data science, or related field (preferred). - Familiar with topics such as distributed and continuum computing, vector databases, performance modeling, storage and memory systems, etc. (preferred). Requirements - Not Applicable for Hazardous Working Conditions/Environment. - This is not a Testing Designated Position (TDP). Benefits - Health insurance - Flexible work schedules - Employee assistance program - Business travel insurance - Company funded pension plan and 401k savings plan (for regular hourly employees) Company Description 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. PNNL is located in eastern Washington State, known for its stellar outdoor recreation and affordable cost of living.

Role Description Research Computing advances scientific discovery by providing researchers computational tools to accelerate their research outcomes. We support computationally enabled science by providing researchers access to computational building blocks (e.g., HPC, Machine Learning environments, Data Management Tools, etc.). We also provide services, expertise, and support to researchers to optimize their use of our capabilities (e.g., HPC & Machine Learning Consulting, and machine Learning workflow management, etc.), all while fostering a culture of computing through interdisciplinary collaboration and access to computational resources. We are seeking an HPC Software engineer to join project teams building HPC and AI/ML solutions to support a broad variety of scientific domains. The scope of work will be diverse and will include: - Joining existing project teams across the research directorates. - Engaging and understanding their domain and project needs. - Designing, building, and implementing applications and pipelines to support their various needs. - Implementing broadly applicable operational solutions to support ranges of projects and domains, including pipelines, automation, containerization, and various technologies and platforms. - Joining existing research efforts and developing software and algorithms to support the project research focus. - Helping domain scientists leverage various ML techniques. You must understand and have experience in a mix of technologies such as Python, C, PyTorch, and OpenMPI. Experience with HPC system engineering is required. For aspects of the work, experience and interest in Machine Learning workflows and large language models will be an advantage. Additionally, it would be advantageous to have experience in other scientific or engineering domains and mathematics. Initially, you will join existing project teams, and as such, you will be expected to operate within specific guidelines and coding standards. As a level 3, you will be increasingly responsible for building your own opportunities within PNNL, leading other team members in developing technical solutions, and developing opportunities for other staff to follow. Additionally, you are expected to mentor others and lead tasks on projects. Qualifications - PhD and 1 year of Software Engineering experience -OR- - MS/MA and 3 years of Software Engineering experience -OR- - BS/BA and 5 years of Software Engineering experience -OR- - AA and 14 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development -OR- - HS/GED and 16 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development. - Experience with HPC software builders, such as Spack. - Knowledge of and experience supporting Slurm. - Experience participating in working with scientists and engineers of various scientific domains and being able to bridge between the various domains and computer and data science. - Experience working with project teams, especially including domain scientists, understanding scientific realms, and applying computer science and mathematical principles in support of the scientific mission of the project. - Experience with building large language models to support research. Requirements - Experience with HPC system engineering. - Understanding of Python, C, PyTorch, and OpenMPI. - Experience and interest in Machine Learning workflows and large language models. Benefits - Medical insurance. - Dental insurance. - Vision insurance. - Robust telehealth care options. - Several mental health benefits. - Free wellness coaching. - Health savings account. - Flexible spending accounts. - Basic life insurance. - Disability insurance. - Employee assistance program. - Business travel insurance. - Tuition assistance. - Relocation assistance. - Backup childcare. - Legal benefits. - Supplemental parental bonding leave. - Surrogacy and adoption assistance. - Fertility support. - Company-funded pension plan. - 401(k) savings plan with company match. - Up to 120 vacation hours per year. - Ten paid holidays per year.

Role Description The Electricity Infrastructure and Buildings Division of PNNL is accelerating the transition to a decarbonized, efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy. The Optimization and Control Group and the Energy Systems and Resilience Group are looking for a Summer Intern to contribute to innovative research on foundational models and cybersecurity. The intern will play a key role in leveraging foundational models to streamline user interactions and provide targeted insights for an existing multi-criteria decision-making platform used in large-scale infrastructure planning. Additionally, the position will also focus on the application of Artificial Intelligence (AI) to develop a set of supplementary tools to enhance the Cybersecurity Capability Maturity Model (C2M2). The intern will work with PNNL staff to: - Simplify user interactions and answer complex infrastructure planning queries for multi-criteria decision making in large-scale infrastructure planning. - Enable users of the C2M2 to advance the maturity of their cybersecurity program. The work will require an understanding of AI training, testing, and validation. Furthermore, the intern may be required to work with PNNL staff in the deployment of the tool. Qualifications - Currently enrolled/matriculated in a PhD program at an accredited college. - Minimum GPA of 3.0 is required. - Preferred: Currently enrolled in PhD program Computer Science, Electrical Engineering, Computer Engineering, Data Science, Cybersecurity, or a closely related field. - Preferred coursework or project experience in: - Machine learning/NLP - Information retrieval - Software engineering - Cybersecurity - Nice-to-have: Relevant certifications or training such as Azure/AWS fundamentals, Security+ (or equivalent), or prior research/industry experience with applied AI. - Intermediate programming ability in Python; familiarity with software engineering basics (Git, code reviews, unit testing, packaging). - Some working knowledge of LLMs and agent frameworks (e.g., OpenAI/Anthropic APIs, Azure OpenAI; LangChain and/or LlamaIndex) including prompt design, tool/function calling, retrieval-augmented generation (RAG), and basic agent orchestration. - Experience with data preparation and knowledge management: - Cleaning/structuring text - Document ingestion - Metadata/tagging - Embeddings - Working with vector databases (e.g., FAISS, Chroma, Pinecone, Azure AI Search, Elasticsearch). - Understanding of AI evaluation, testing, and validation: - Creating test sets - Measuring response quality/accuracy - Hallucination and bias considerations - Regression testing for prompts/agents - Documenting limitations. - Familiarity with cybersecurity concepts sufficient to work with C2M2 content (e.g., governance, risk management, asset management, incident response); ability to learn the C2M2 model quickly and translate it into user workflows. - Basic experience or understanding building web apps or APIs for deployment/integration (e.g., Flask/FastAPI, Streamlit, or similar), plus containerization fundamentals (Docker) and cloud/service deployment awareness. - Strong written communication and documentation skills (requirements capture, design notes, user guidance), ability to collaborate with researchers/engineers, and comfort working with sensitive information under defined controls. Requirements - Not Applicable Benefits - Employee assistance program - Business travel insurance - Company funded pension plan and 401k savings plan (once eligibility requirements are met) Company Description 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, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living.

Role Description At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. The Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing: - Artificial intelligence - Applied mathematics - Computing technologies - Data and computational engineering Our scientists and engineers apply end-to-end co-design principles to advance future energy-efficient computing systems and design the next generation of algorithms to analyze, model, understand, and control the behavior of complex systems in science, energy, and national security. Responsibilities - Data Preparation & Analysis: - Clean, transform, and integrate structured and unstructured datasets and documents, including equipment datasheets and ArcGIS-based spatial data, from environmental and energy systems domains. - Power Grid Systems, Simulation & Resilience: - Knowledge of power grid systems and resilience, with experience applying agentic AI to model power grid simulations, analyze grid-related problems, and support more efficient and reliable operational decision-making. - Data Engineering & Pipeline Architecture: - Design scalable data systems (ETL, data lakes, data meshes) that support large-scale legislation, regulatory, and legal document workflows. - Software Engineering & DevOps: - CI/CD, testing, version control, and open-source practices enabling reliable, reproducible systems across research and production. - Computer Vision & Image Analysis: - Develop and apply computer vision methods for crystallography workflows and metadata processing, including image analysis, object detection, tracking, segmentation, and automated interpretation, to enable automation of light source beamline operations in scientific and real-world environments. - Generative AI & Foundation Models: - Development and evaluation of large-scale generative AI systems, including fine-tuning, agents, tool use, and optimization for robustness, alignment, and efficiency. - Agentic AI Systems & Autonomous Workflows: - Design and deploy scalable agentic AI systems with autonomous workflows, dynamic tool use, and complex decision-making to support advanced scientific and operational tasks. Qualifications - Minimum Qualifications: - Candidates must have received a Master’s degree within the past 24 months or within the next 8 months from an accredited college or university. - Preferred Qualifications: - Masters degree in Computer Science, Data Science, Applied Mathematics, Electrical Engineering, Computational Engineering, or a closely related field. - Prior research experience, including internship experience within a national laboratory setting. - Experience in data preparation, integration, and applications involving large language models. - Strong technical computing skills in Python, with proficiency in NumPy or similar scientific computing frameworks. - Ability to translate ambiguous or evolving technical objectives into clear, actionable analytical approaches. - Experience working in applied research settings or collaborative R&D environments. - Demonstrated ability to work effectively within interdisciplinary and geographically distributed teams, using a collaborative and solutions-oriented approach. Benefits - Medical insurance - Dental insurance - Vision insurance - Robust telehealth care options - Several mental health benefits - Free wellness coaching - Health savings account - Flexible spending accounts - Basic life insurance - Disability insurance* - Employee assistance program - Business travel insurance - Tuition assistance - Relocation - Backup childcare - Legal benefits - Supplemental parental bonding leave - Surrogacy and adoption assistance - Fertility support - Company-funded pension plan* - 401(k) savings plan with company match* - Up to 120 vacation hours per year - Ten paid holidays per year Company Description 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. 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.

Role Description At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. The Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing artificial intelligence, applied mathematics, computing technologies, and data and computational engineering. - Aggregate, transform, and integrate structured and unstructured datasets and documents into a central, structured database. - Knowledge of environmental and power grid systems, with experience analyzing and organizing power grid data. - Development and evaluation of large-scale generative AI workflows for material science applications. - Design and deploy scalable agentic AI systems with autonomous workflows. - Design of scalable data systems to support large-scale scientific and production workflows. - Development and evaluation of DataMesh-style scientific retrieval systems. Qualifications - Master’s degree within the past 24 months or within the next 8 months from an accredited college or university. - Masters degree in Computer Science, Data Science, Applied Mathematics, Electrical Engineering, Computational Engineering, or a closely related field. - Prior research experience, including internship experience within a national laboratory setting. - Experience developing or experimenting with agentic systems or machine learning methods. - Experience with developing data pipelines to extract and aggregate relevant information. - Strong programming experience in C++, and/or Python. - Strong written and verbal communication skills. - Experience working in collaborative and interdisciplinary research environments. Requirements - Not Applicable for Hazardous Working Conditions/Environment. - This is not a Testing Designated Position (TDP). Benefits - Medical insurance, dental insurance, vision insurance. - Robust telehealth care options, several mental health benefits. - Free wellness coaching, health savings account, flexible spending accounts. - Basic life insurance, disability insurance, employee assistance program. - Business travel insurance, tuition assistance, relocation, backup childcare. - Legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. - Company-funded pension plan and 401(k) savings plan with company match. - Up to 120 vacation hours per year and ten paid holidays per year. Company Description 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. At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules.

Role Description PNNL's Future Computing Technologies group seeks an accomplished Post Doctoral Researcher to explore hardware-software codesign methodologies for the future computing systems that will meet the needs of scientific computing. Relevant research topics include: - Novel methods for hardware-software codesign, including workload characterization, performance modeling, and architectural emulation. - Memory-centric toolsets for modeling and optimizing software and architectures. - Forming disaggregated memory-storage systems through fabric-attached memory (FAM) technologies such as Compute Express Link (CXL). - Scaling AI workloads (inference, training, agentic workflows), irregular and data-intensive applications, and managing geo-distributed datasets. The successful applicant will work within the Future Computing Technologies group and have demonstrated expertise in a topic closely related to continuum computing, distributed and parallel computing, memory and storage systems, performance and workload modeling, telemetry, and characterization. The researcher should be creative, self-motivated, and familiar with publishing at top-tier venues. Qualifications - Minimum Qualifications: - Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university. - Preferred Qualifications: - PhD in Computer Science, Computer Engineering, Electrical/Computer Engineering, Applied/Computational Mathematics, Data Science, or a closely related field. - Familiar with topics such as distributed and continuum computing, vector databases, performance modeling, storage and memory systems, etc. Requirements - This is not a Testing Designated Position (TDP). Benefits - Medical insurance - Dental insurance - Vision insurance - Robust telehealth care options - Several mental health benefits - Free wellness coaching - Health savings account - Flexible spending accounts - Basic life insurance - Disability insurance* - Employee assistance program - Business travel insurance - Tuition assistance - Relocation - Backup childcare - Legal benefits - Supplemental parental bonding leave - Surrogacy and adoption assistance - Fertility support - Employees are automatically enrolled in our company-funded pension plan* - 401(k) savings plan with company match* - Up to 120 vacation hours per year - Ten paid holidays per year Company Description 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. At PNNL, you will find an exciting research environment and excellent benefits including health insurance and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living.

Role Description PNNL's Future Computing Technologies group seeks an accomplished Post Doctoral Researcher to explore methods for the characterization, modeling, and orchestration of AI-assisted scientific workflows; the scalable and efficient orchestration of workflows on mixtures of HPC and cloud resources; the management of distributed datasets. Relevant research topics include: - Seamless hybrid computing: Enabling adaptive workflows and pipelines that seamlessly bridge and span DOE's HPC, private-cloud and federated data sources. - Agentic scientific workflows: Effectively mapping agentic workflows to the most appropriate DOE cloud and HPC resources while managing access to sensor inputs and facilitating intelligent interactions with remote datasets. - Quality-of-service for science: Ensuring workflow-enabled experiments observe, assess, and react under hard time constraints. Allowing scientists to specify computing policies to ensure that live scientific experiments obtain only the necessary compute resources for making time-critical decisions. The successful applicant will work within the Future Computing Technologies group and have demonstrated expertise in a topic closely related to continuum computing, distributed and parallel computing, memory and storage systems, performance and workload modeling, telemetry, and characterization. The researcher should be creative, self-motivated, and familiar with publishing at top-tier venues. Qualifications - Minimum Qualifications: Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university. - Preferred Qualifications: - PhD in Computer Science, Computer Engineering, Electrical/Computer Engineering, Applied/Computational Mathematics, Data Science, or a closely related field. - Familiar with topics such as distributed and continuum computing, vector databases, performance modeling, storage and memory systems, etc. Requirements - Not Applicable for Hazardous Working Conditions/Environment. - This is not a Testing Designated Position (TDP). Benefits - Medical insurance - Dental insurance - Vision insurance - Robust telehealth care options - Several mental health benefits - Free wellness coaching - Health savings account - Flexible spending accounts - Basic life insurance - Disability insurance* - Employee assistance program - Business travel insurance - Tuition assistance - Relocation - Backup childcare - Legal benefits - Supplemental parental bonding leave - Surrogacy and adoption assistance - Fertility support - Company-funded pension plan* - 401(k) savings plan with company match* - Up to 120 vacation hours per year - Ten paid holidays per year Company Description 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. 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.

Role Description The Computational Mathematics Group at PNNL is seeking a motivated Undergraduate Summer Intern with a strong foundation in applied mathematics, preferably with experience or interest in graph theory and randomized algorithms. This internship offers an opportunity to contribute to cutting-edge research in network science. - Develop and apply randomized algorithms to scientific problems. - Work with standard software packages for graphs and hypergraphs. - Collaborate with internal research staff to support ongoing projects and share insights. This position is ideal for students who are passionate about applying mathematical and computational techniques to real-world scientific challenges. Qualifications - Minimum Qualifications: - Candidates must have a high school diploma /GED or higher. - Candidates must be degree-seeking undergraduate students enrolled at an accredited college or university. - Candidates must be taking at least 6 credit hours and have an overall cumulative GPA of 2.5. - Preferred Qualifications: - Pursuing an undergraduate degree in Mathematics, Applied Mathematics, Computational Mathematics, or related degree. - Experience in graph theory, combinatorial programming, randomized algorithms. - Experience writing results for the broader mathematical community. Requirements - Not Applicable. Benefits - Employees are offered an employee assistance program and business travel insurance. - Employees are eligible for the company funded pension plan and 401k savings plan, once eligibility requirements are met. Company Description 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, and flexible work schedules. 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.

Role Description DOE’s Office of Environmental Management Graduate Fellowship Program is seeking graduate fellows to work on some of the nation’s greatest cleanup efforts. The successful candidate will join other postdocs and graduate fellows as part of the Minority Serving Institutions Partnership Program (MSIPP). MSIPP is funded by the Department of Energy Office of Environmental Management (DOE-EM). The selected candidate will work on projects related to environmental data processing, analysis methods, statistical modeling, data visualizations, and AI tool development. - Work with a wide range of types and formats of environmental data spanning geophysics, groundwater chemistry, water levels, remote sensing, etc. to condition and analyze data to identify trends and insights to support environmental remediation decision-making. - Apply statistical, machine learning, and artificial intelligence approaches and methods to develop insights to the remediation process or tools that can guide the remediation process. - Manage and organize large datasets to maintain data integrity and accessibility, meeting data validation and quality assurance objectives. - Collaborate with environmental/chemistry experts, engineers, software developers, and data scientists to understand specific project goals and execute on project/task delivery. Qualifications - Minimum Qualifications: - Candidates must have received a Master’s degree within the past 24 months or within the next 8 months from an accredited college or university. - Minimum GPA of 3.0 is required. - Preferred Qualifications: - Degree in Data Science, with education (Minor or certificate) related to statistical analysis/modeling. - Proficiency in math/data analytics and data science (e.g., statistics, Artificial Intelligence/Machine Learning), including analysis using Tableau. - Coding experience with Python, JavaScript, and SQL (R or VBA are a bonus). - Experience with Amazon Web Services cloud computing, including serverless and AI services. - Ability to work collaboratively in team settings, along with excellent verbal and written communication skills. - Experience with data/software quality assurance programs (e.g., NQA-1). - Strong familiarity with and interest in cleanup/environmental management and associated challenges. Requirements - This position involves access to sensitive systems and information. U.S. Citizenship is required. - Pacific Northwest National Laboratory is subject to the Department of Energy Unclassified Foreign Visits & Assignments Program site, information, technologies, and equipment access requirements. Benefits - Medical insurance - Dental insurance - Vision insurance - Robust telehealth care options - Several mental health benefits - Free wellness coaching - Health savings account - Flexible spending accounts - Basic life insurance - Disability insurance* - Employee assistance program - Business travel insurance - Tuition assistance - Relocation - Backup childcare - Legal benefits - Supplemental parental bonding leave - Surrogacy and adoption assistance - Fertility support - Employees may accrue up to 120 vacation hours per year - Employees may receive ten paid holidays per year