Predoctoral Appointee - Data Reduction with ASIC AI Accelerators
Argonne National Laboratory
Lemont, USA
Job posting number: #7234030 (Ref:417857)
Posted: April 2, 2024
Job Description
The Advanced Photon Source (APS) (https://www.aps.anl.gov/) and Mathematics and Computer Science (https://www.anl.gov/mcs) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a pre-doctoral position to develop data reduction methods with low-latency ASIC AI accelerators. At Argonne, we have demonstrated millisecond-scale data reduction using networked, commodity edge processing units (https://www.nature.com/articles/s41467-023-41496-z). This new project aims to develop low-latency (microsecond-scale) data reduction methods to run on state-of-art ASIC AI accelerators which are tightly coupled to scientific detectors. Such as a workflow will enable on-the-fly scientific data analysis, autonomous experiments, and instrument tuning. Finally, the project aims to architect a detector system with an edge co-processor chiplet and high bandwidth memory using interposer technologies. In conjunction, the project aims to develop compression algorithms based on physics-informed neural networks (PINN) that are trained to recognize the noise distribution in detector images.
The successful candidate will be part of an international, highly inter-disciplinary team of experts in ASIC and FPGA design, data reduction and X-ray detector development. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris, Aurora) and one of the brightest synchrotron x-ray sources in the world (APS-U).
Position Requirements
Required Knowledge, Skills and Experience:
Master's degree in electrical engineering, computer engineering, machine learning, computational physics, image processing, x-ray science or a related field
Combination of expertise with computing/software and digital logic (firmware) design from the algorithmic level to the hardware implementation.
Knowledge of digital logic designs (RTL) using System Verilog.
Python programming.
Experience with building digital test-benches and carry-out digital circuit simulations.
Ability to work effectively as a member of a team.
Ability to effectively communicate with people of diverse backgrounds and skill sets.
Understand, value, and promote diversity.
Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Preferred Knowledge, Skills and Experience:
Advanced digital verification techniques using System Verilog and UVM methodologies.
Experience working with Scala, Chisel and FIRRTL methodology.
Experience with deep learning libraries (Keras, Tensorflow, PyTorch etc.)
Experience with FPGA designs.
Job Family
Temporary FamilyJob Profile
Predoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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