The Applied Mathematics Department of the Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for the Amalie Emmy Noether Fellowship in applied mathematics and scientific computing. Differentiating it from other project-supported postdoctoral positions, the prestigious Noether Fellowship comes with partial funding to pursue independent research of the fellow’s design, under the mentorship and aligned with the mission of applied mathematics at BNL. This fellowship offers a unique opportunity to conduct research in a broad set of fields, including decision making under uncertainty, scientific machine learning, reduced order or surrogate modeling, optimization, optimal experimental design, uncertainty quantification and scalable computational statistics, high-dimensional inverse problems, streaming/parallel/distributed data analytics for high performance computing (HPC), integrated computational/experimental scientific campaign design and management, numerical methods, and multiscale modeling and simulation.
The methods and fundamental advances made in the course of this research will further the progress of applications of interest to BNL and the Department of Energy (DOE). Examples of such mission areas include climate science and climate resilience, design of nanomaterials, low-dose radiation biology, drug discovery, biosecurity, particle accelerator design and control, nuclear physics, quantum computing, power grid resilience, and automation and optimal control of DOE experimental user facilities, among others.
The fellowship includes access to world-class HPC resources, such as the BNL Institutional Cluster and DOE leadership computing facilities. Access to these platforms will allow computing at scale and will ensure that the successful candidate will have the necessary resources to solve challenging DOE problems of interest.
This position provides support for a period of two years at CSI. This fellowship presents a unique chance to conduct interdisciplinary collaborative research in BNL programs with a highly competitive salary. Recipients will be allowed to select a direct mentor from a list of CSI staff scientists. This mentor will help the recipient define and pursue their own research agenda during their appointment.
Essential Duties and Responsibilities:
• Conduct research in applied mathematics
• Work in interdisciplinary collaborations with other mathematicians and applied domain scientists
• Formulate an independent, high-quality research program in collaboration with lab mentors
Required Knowledge, Skills, and Abilities:
• Ph.D. in applied or computational mathematics or a related field (e.g., mathematics, engineering, physics, statistics, operations research, computer science)
• Programming experience in scientific computing
Preferred Knowledge, Skills, and Abilities:
Knowledge in one or more of:
• Experience solving applied domain sciences problems (e.g., in physical sciences, life sciences, or engineering)
• Experience working in interdisciplinary collaborations
• Scientific machine learning
• Model reduction or surrogate modeling
• Decision making under uncertainty or optimal design of experiments
• Optimization
• Bayesian inference, uncertainty quantification, spatiotemporal statistics, or scalable computational statistics
• High performance computing
• Modeling and simulation
• Numerical methods
Other Information:
• BNL policy requires that after obtaining their PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events.
• The initial two-year term appointment is subject to renewal contingent on performance and funding.
Compensation:
Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $70200 - $116200 / year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.
