As a Scientific Computing graduate student, Wenju Zhao attended a summer internship at Lawrence Livermore National Laboratory (LLNL) in Livermore, California near the San Francisco Bay area. LLNL is a world class federally funded science lab; its principle responsibility is to ensure the safety, security and reliability of the nation’s nuclear weapons. Each year, a large number of summer students are invited to participate in various research projects with scientists. This direct research experience is an unparalleled opportunity for undergraduate and graduate student to experience and understand first hand working in a premier research lab.
“I received this excellent opportunity because of Professor Max Gunzburger. He recommended me for the internship to Dr. Xiao Chen,”
said Zhao. Chen, a former student of Professor Michael Navon, is a Computational Scientist and Project Leader in the Center for Applied Scientific Computing at LLNL. In fact, Zhao commented on the prevalence of SC alum currently employed at national laboratories, and the importance of using those established networks to find internship and job opportunities.
“I learned that many of our department alumni work at Livermore and other world class labs -- Oak Ridge, Sandia, Los Alamos. They also work at other very well-known companies and organizations. It is important to keep in touch with our alumni to learn of positions and obtain job recommendations.”
Zhao spent his summer internship attempting to develop an algorithm and software to solve stochastic inverse elasticity problems, which have complicated and advanced practical significance and applications.
Zhao observed. Mathematically, the project required a wide range of knowledge, including PDE and SDE, PDE constrained optimal control, and uncertainty quantification. Zhao also engaged his skills in high performance computing, C++, Fortran, and Python. All simulations were done on Livermore’s most advanced computing systems.
“We used inverse elasticity problems because we wanted to try to determine the elastic properties of subsurface formations based on some experimental observation data. This kind of stochastic inverse problem is very challenging due to sparse observations, noisy measurement and the high heterogeneous nature of the underground structures,”
Several differences between a university and laboratory environment were apparent to Zhao as soon as he arrived.
Because of the interdisciplinary nature of the research, Zhao collaborated with a host of scientists from different divisions. Zhao worked with computational scientist Charles Tong from the Center for Applied Scientific Computing, geoscientist Joshua White from the Atmospheric, Earth and Energy division, LLNL postdoc Charanraj Thimmisetty (UQ) from UCLA, and Xiao Chen. Near the end of his time in California, Zhao displayed a poster and gave a presentation of his work.
“When it comes to real applications, it is always an interdisciplinary undertaking. At the lab, scientists aim to address real world applications. The data are usually very large and the collaborations are always across several research fields.”
All in all, it was an enjoyable and fruitful summer for Zhao at LLNL, and he encourages others to apply for future opportunities.
“Livermore was a good place to meet people from different research fields and learn how to collaborate with others. Life at the lab is colorful. They have lots of seminars and BBQs and you get to meet different people from different research fields. During weekends, it is a wonderful experience to take a bird's-eye view of San Francisco from the north entrance of the Golden Gate bridge driving California State Route 1 along the Pacific Ocean and have a visit to visit Silicon Valley. To the east of the lab, you can go surfing and swimming in Lake Tahoe and see Yosemite waterfalls - the highest in North America.”
“The courses available in our department definitely made me well prepared for this position. I encourage other students in our department to apply. I would be glad to provide suggestions to help others be successful.”Wenju Zhao