Join Pacific Northwest National Laboratory (PNNL) as we participate in the Tapia Conference in September.
Researchers at PNNL combine profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, PNNL connects research to engineering to operations, providing the tools necessary to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.
Come by our virtual booth to learn more about what it’s like to work for a national laboratory and the exciting research and development we do. Researchers, managers, and recruiters will be on hand throughout the day to answer your questions and speak with you about opportunities.
September 15, 1:30–2:15 PM CDT
Sumit Purohit (PNNL), Meg Duba (INL), Madalynn Miller (ORNL), Jesse Martinez (LANL), Frank Trigueros (LLNL), Ben Lenard (ANL)
What is a national laboratory? Do they offer internships? Do they employ non-U.S. Citizens? What is scientific computing? How can I learn more about supercomputing?
This interactive discussion and information session is for anyone actively exploring and educating themselves about diverse career path options and looking for gems of opportunity in terms of internships, funding programs, and research or postdoc programs. Presenters will discuss the importance of the student internship (and of including a broad set of internship experiences, if possible) in shaping a career path. The presenters will answer “What is a National Laboratory?” among other questions, and discuss how a national laboratory experience can provide unique exposure, training, perspective, and skill development to help shape career path and direction with perhaps unexpected and amazing results.
September 15, 4:45–5:30 PM CDT
Vikas Chandan (PNNL), Sam Jacobs (LLNL), David Lawrence (JLAB), Marisa Torres (LLNL)
Sumit Purohit (PNNL), Celeste Matarazzo (LLNL)
Data science is the process of using algorithms, methods, and systems to extract knowledge and insights from structured and unstructured data. Data science is not just about data—it is a multidisciplinary field that brings together computer science, statistics, artificial intelligence, network science and many others. The advancement in data science technologies is increasing rapidly with each year with many developments in research, platforms, tools, and applications. This session gathers researchers from US Department of Energy national laboratories to discuss their experiences and current applications of data science. Discussion topics will include a variety of applications such as machine learning based data quality monitoring in nuclear physics, machine learning advancements for accelerated design of medical therapeutics, and machine learning for decarbonizing buildings through modeling, control, and optimization.
September 16, 1:30–2:15 PM CDT
Stacey Hartley-McBride (PNNL), Charisa Powell (NREL), Ryan Carey (NREL), Andrew Bochman (INL), Meg Duba (INL), Amanda Joyce (ANL), Jini Ramprakash (ANL), Patrick Avery (LANL), Rima Asmar Awad (ORNL)
Critical infrastructure sectors are ones whose assets, systems, and virtual and physical networks are considered so vital to the United States that their damage or destruction would be catastrophic to our nation’s security, economy, and/or public health.
The US Department of Energy’s national laboratories perform scientific research and analyses to help secure our nation’s infrastructure. This session will explore some of those approaches to serve as a lens to the impactful innovation performed at national laboratories. Topics will include the recent high-visibility cyber-attacks targeting the Colonial Pipeline and an attempt to poison the water supply at a water utility in Florida.
September 16, 4:45–5:30 PM CDT
Kevin Brown (ANL), Carolyn Marie Connor (LANL), Veronica Melesse Vergara (ORNL), Timothy Kaiser (NREL), Thomas MacKell Jr. (LANL), Thomas Papatheodore (ORNL), Jini Ramprakash (ANL)
High-performance computing (HPC) has broad applicability in various scientific domains. The US Department of Energy (DOE) national laboratories house some of the most powerful HPC centers in the world along with deep staff expertise to support ground-breaking science and engineering.
In this session speakers with significant HPC experience at DOE will introduce the audience to the following topics:
Attendees will walk away from this session with pointers to useful tutorials and materials that will provide ways to gain deeper knowledge of HPC.