Post Doctorate Research Associate- Agentic Workflows and Hybrid Scalable Computing

Pacific Northwest National Laboratory

14h • $69,000 - $119,100

About The Position

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. How can we enable adaptive workflows and pipelines that seamlessly bridge and span DOE's HPC, private-cloud and federated data sources? Agentic scientific workflows. How can we effectively map agentic workflows to the most appropriate DOE cloud and HPC resources while also managing access to sensor inputs and facilitating intelligent interactions with remote datasets? Quality-of-service for science. Workflow-enabled experiments must observe, assess, and react under hard time constraints. How can scientists easily specify computing policies to ensure that live scientific experiments obtain only the necessary compute resources for making time-critical decisions? The policies should meet deadlines while also permitting maximum scheduling flexibility. 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.

Requirements

• Received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.
• 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.
• Creative, self-motivated, and familiar with publishing at top-tier venues.
• 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.

Responsibilities

• Explore methods for the characterization, modeling, and orchestration of AI-assisted scientific workflows.
• Explore scalable and efficient orchestration of workflows on mixtures of HPC and cloud resources.
• Explore the management of distributed datasets.
• Enable adaptive workflows and pipelines that seamlessly bridge and span DOE's HPC, private-cloud and federated data sources.
• Effectively map agentic workflows to the most appropriate DOE cloud and HPC resources while also managing access to sensor inputs and facilitating intelligent interactions with remote datasets.
• Ensure that live scientific experiments obtain only the necessary compute resources for making time-critical decisions.
• Meet deadlines while also permitting maximum scheduling flexibility.

Benefits

• health insurance
• flexible work schedules
• 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
• 120 vacation hours per year
• ten paid holidays per year

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees