Postdoctoral Scholar - Applied Mathematics Department (Computational Research)
Lawrence Berkeley National Laboratory
June 6, 2018
Berkeley, United States
The Applied Mathematics Department in the Computational Research Division (crd.lbl.gov) is looking for talented and motivated postdoctoral fellows to become part of our team working on exciting research projects in applied mathematics and scientific computing. Researchers in applied mathematics and scientific computing, or any relevant discipline, who have received their Ph.D. within the last three years are encouraged to apply. The successful applicant will receive a competitive salary and excellent benefits.
The Applied Mathematics Department develops advanced mathematical models and efficient computational algorithms for solving a broad range of scientific and engineering problems of interest to the Department of Energy (DOE), including in particular those related to energy and environment. Some of the current scientific and engineering areas include accelerator physics, astrophysics, climate, combustion, and seismic imaging. Many of the algorithms have scalable implementations that are targeted at current and next-generation massively parallel computer architectures, such as those available at the DOE National Energy Research Scientific Computing Center. Some of the implementations are also available in the form of the user-callable software frameworks and libraries. More details on the activities and projects in the Applied Mathematics Department can be found at http://crd.lbl.gov/departments/applied-mathematics/.
The successful applicant will be part of one of the research teams in the department working on a wide range of research and development projects and will join one of the three groups in the Applied Mathematics Department. These groups and their mission/focus, together with their current activities, are listed below.
The Applied Numerical Algorithms Group (ANAG) develops advanced numerical algorithms and software for solving the partial differential equations which arise in problems of scientific and engineering interest. The primary focus of our work is in the development of high-resolution and adaptive finite volume/difference methods for partial differential equations in complex geometries with applications in a diverse range of fields such as compressible and incompressible fluid flows, plasma physics, porous-media flows, ice sheet modeling, carbon sequestration, climate, and astrophysics. The group's primary software product is Chombo, an open-source publicly distributed scalable adaptive mesh refinement (AMR) library that incorporates solver technologies developed in the group. These technologies include hyperbolic and elliptic solvers, PIC methods, and embedded boundary and mapped-multiblock approaches to complex geometries. Chombo is used regularly on platforms ranging from laptops to leadership-class supercomputer systems.
Ongoing efforts in the group fall into two broad categories. One is the development of novel algorithms, with a current focus on the design and implementation of higher order adaptive finite-volume methods more suitable for emerging architectures than existing algorithms. The second broad area involves working closely with the colleagues in CS research to incorporate and interface with developments in programming abstraction and other HPC matters. In these areas the current thrust is on DSLs, auto-tuning, asynchronous task scheduling and resiliency.
The Center for Computational Sciences and Engineering (CCSE) develops and applies advanced computational methodologies to solve large-scale scientific and engineering problems arising in DOE mission areas involving energy, environment, and industrial technology. The primary focus of CCSE researchers is on designing algorithms for multiscale, multiphysics problems described by nonlinear systems of partial differential equations, and in developing implementations of algorithms that target current and next-generation massively parallel computational architectures. CCSE researchers work collaboratively with application scientists to develop state-of-the-art solution methodologies in these fields.
In recent years, application areas have included combustion, porous media flow, mesoscale models for hydrodynamics, atmospheric modeling, cosmology and astrophysics. A common theme in a number of CCSE projects is low Mach number methods for weakly compressible flows, and the use of block-structured adaptive mesh refinement. Combustion efforts have focused on direct numerical simulation of laboratory-scale turbulent flames using detailed models for chemical kinetics. In the area of mesocale fluid mechanics we are developing stochastic continuum models that represent thermodynamic fluctuations in hydrodynamic variables and hybrid algorithms that combine continuum and particle descriptions of a fluid. We have also begun a new project area in which we are integrating simulation and experimental data to improve predictions of the behavior of complex systems.
The Mathematics Group develops new mathematical models, devises new algorithms, explores new applications, exports key technologies, and trains young scientists in support of DOE. We use mathematical tools from a variety of areas in mathematics, physics, statistics, and computer science, including statistical physics, differential geometry, asymptotics, graph theory, partial differential equations, discrete mathematics, and combinatorics. Rather than focus on a specific software or algorithmic approach, our orientation is to invent, implement, and use appropriate mathematics to tackle a range of scientific and engineering problems.
In recent years, application areas have included complex simulations of semiconductors, coating rollers, inkjet printing technologies and microfluid effects, foams in manufacturing processes, new metals, granular mixers, coal hoppers, rolling tires, mode-locked lasers, wind turbines, vibrating RF MEMS devices for wireless communications, and dynamic fracture in bulk metallic glasses. Another set of topics focuses on tools for the analysis of energy processes, and includes stochastic methods in environmental science, data analysis for meteorological data, data synthesis for wind energy and large-scale ocean currents, seismic imaging, image processing and analysis for analyzing cellular structures, and complex fluid-membrane solvers for understanding the dynamics behind cellular development in new biofuels and path planning for determining chemical accessibility in new materials such as zeolite and metal organic frameworks for gas separation sieves in carbon sequestration.
The successful candidate will have excellent oral and written communication skills; have a strong technical background in applied mathematics or scientific computing and be able to work effectively both in an independent fashion as well as part of a team.
The Scalable Solvers Group (SSG) develops and implements state-of-the-art algorithms for solving large-scale algebraic systems, including, but not limiting to, systems of linear equations, systems of nonlinear equations, and eigenvalue problems, on massively parallel computer architectures. Many of the algorithms are available and have been distributed in the form of software packages. By collaborating with domain scientists, the group applies the algebraic solvers developed to solve a variety of scientific problems that are central to the mission of DOE.
In recent years, the emphases have included scalable large sparse direct solvers, parallel multi-grid solvers, sparse eigenvalue solvers, randomized algorithms in numerical linear algebra, and fast sparse linear equations solvers based on data compression. Much of work is driven by the needs in the solution of large-scale scientific problems, which require close interaction and collaboration with domain scientists.
Research and development of mathematical models of physical phenomena
Implementation of new and existing algorithms, tools and technologies for tackling scientific and engineering problems
Evaluation of existing and new techniques
Work in a multidisciplinary team environment including mathematicians, computer/computational scientists, and domain scientists
Author peer-reviewed journal articles and contribute to research proposals
Ph.D. in Applied Mathematics, Computer Science, or the Physical Sciences/Engineering within the last 3 years, with a strong research background in applied mathematics, computational methods, and scientific computing
Keen interest in solving mathematical and scientific computing problems
Additional Desired Qualifications:
Experience in parallel computing and programming experience in C, C++, and Fortran preferred, as well as MPI and OpenMP
Experience as part of a multidisciplinary, collaborative team that includes mathematicians, computer/computational scientists and domain scientists
The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on December 20, 2018.
Notes: We encourage all applicants to provide a cover letter and a statement of research interests when applying.
This is a full time two-year postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years paid postdoctoral experience. Salary for postdoctoral positions depends on years of experience post-degree.
Full-time, M-F, exempt (monthly paid) from overtime pay.
This position is represented by a union for collective bargaining purposes.
Salary will be predetermined based on postdoctoral step rates.
This position is contingent on the successful completion of a background check.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."
Internal Number: 85173
About Lawrence Berkeley National Laboratory
In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) is synonymous with excellence. Thirteen scientists associated with Berkeley Lab have won the Nobel Prize. Fifty-seven Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation's highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world. Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 200-acre site in the hills above the UC Berkeley campus that offers spectacular... views of the San Francisco Bay, Berkeley Lab employs approximately 4,200 scientists, engineers, support staff and students. Its budget for 2011 is $735 million, with an additional $101 million in funding from the American Recovery and Reinvestment Act, for a total of $836 million. A recent study estimates the Laboratory's overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars. Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a UC Berkeley physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence's belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.