Postdoctoral Appointee - Materials, Circuits and Computer Systems
- Argonne National Laboratory
- Location: Lemont, IL
- Job Number: 7087392
- Posting Date: Oct 19, 2021
- Application Deadline: Open Until Filled
Job DescriptionThe Mathematics and Computer Science Division seeks a postdoctoral appointee to drive cross-disciplinary simulation in a co-design effort spanning materials to HEP detectors. The incumbent will be a key contributor in a multidisciplinary co-design team that spans materials, circuits, and system-level with the goal of revolutionizing capability for high-energy physics (HEP) and nuclear physics (NP) detectors and associated science. The Postdoc will work with leading scientists to create models at circuit/network, spiking neural networks, and computing system levels. The role includes participation and dissemination of research results at scientific conferences.
The position is in the Mathematics and Computer Science Division (MCS) at Argonne National Laboratory. Argonne is a US Department of Energy Laboratory with world class research in materials, devices, and computing.
The MCS Division includes experts across computer science, applied math, data science and learning, and computational science. The laboratory is the home of a DOE Leadership Computing Facility which will be home to an exascale computing system, and is already equipped with cutting edge machine-learning accelerators such as Cerebras CS-1, Sambanova, Nvidia DGX-A100, and many other advanced computing systems. MCS has active collaborations with over a dozen top computer science departments in the US and around the world.
Postdoctoral appointees will be fully integrated in the large research community in the MCS Division (more than 100 scientists and postdocs) and have the opportunity to collaborate with leaders in the field. This project involves collaboration with two divisions, one of which is the Materials Science Division (MSD) that includes research on superconducting and magnetic materials, quantum metamaterials, ferroelectrics, correlated oxides and catalytic materials, along with new thrusts in topological materials and electrochemical oxides. The second is the High Energy Physics Division (HEP) that have contributed to the deep understanding of the natural world and have built some of the world’s largest, most complex and sophisticated devices, including powerful accelerators, massive particle detectors and sensitive cosmological survey instruments.
Required skills include experience with computational modeling of device and circuits and analysis of computer systems performance. Skills or experience with neuromorphic computing/spiking neural networks and either physics-based device models or computer architecture is highly desirable. Familiarity with parallel or high-performance computing and Linux-based systems are all a plus.
Candidates must have a PhD (typically completed within the last 3 years, or soon-to-be completed) in Electrical or Computer Engineering, or a closely related discipline or equivalent experience.
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