What are the responsibilities and job description for the Postdoctoral Scholar in Sparse Computations and Parallel Computing position at Berkeley Lab?
Lawrence Berkeley National Lab’s ( LBNL ) Applied Mathematics and Computational Research Division has an opening for a Postdoctoral Scholar to join the team.
In this exciting role, you will conduct fundamental and applied research in sparse computations related to matrices, graphs, hypergraphs, simplicial complexes, artificial intelligence and tensors.
What You Will Do
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer
In this exciting role, you will conduct fundamental and applied research in sparse computations related to matrices, graphs, hypergraphs, simplicial complexes, artificial intelligence and tensors.
What You Will Do
- Perform fundamental research in sparse matrix, sparse tensor, and sparse network algorithms.
- Design parallel algorithms for sparse computations in one or more of the three broad domains listed above.
- Implement parallel algorithms for HPC systems.
- Gain familiarity with scientific applications and scientific AI workloads involving sparse computations.
- Publish and present research results in high-impact journals and top conferences in one or more of the following areas: parallel computing, graph algorithms, sparse matrix computations, computational topology, geometric learning.
- PhD degree, within the last 3 years, in Computer Science, Computational Sciences, Applied Mathematics, or a related technical field.
- Proficiency in C , as well as one or more of the parallel libraries/languages: MPI, OpenMP, CUDA.
- Ability to design and implement parallel algorithms for parallel computing, graph algorithms, sparse matrix computations, computational topology, and geometric learning.
- Ability to publish in top journals and conferences.
- Ability to conduct research in a highly collaborative environment.
- Excellent verbal and written communication skills.
- Software engineering tools: make, cmake, revision control systems (such as git).
- One or more of the popular scripting languages such as Python and Julia.
- Familiarity with sparsification techniques, such as sampling, sketching, etc.
- Working experience with sparse data structures
- This is a full-time, 2 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 of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
- This position is represented by a union for collective bargaining purposes.
- The monthly salary range for this position is $8,321-$9,646 and is expected to start at $8,321 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.
- This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
- Work may be performed on-site, or hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer
