Neuromorphic Computing Postdoctoral Scholar
Berkeley Lab’s Applied Mathematics and Computational Research Division (AMCR) has an opening for a Postdoctoral Scholar to develop novel frameworks for brain-inspired neuromorphic computing. Areas of interest are broad and include adaptive processing in dynamically self-reconfiguring neuronal networks, coordination of large scale distributed computation as well as energy efficient neuromorphic hardware.
Brains have the astonishing ability to flexibly change and adapt their function "on the fly" to cope with dynamic environments, changing contexts or varying goals and rewards. Such flexible computations typically require the interaction of a large number of subnetworks which must coordinate communication and computation dynamically. It is hypothesized that the prevalent oscillatory dynamics in the brain provide a substrate to flexibly coordinate computation. This provides guidance for novel directions to develop frameworks for flexible neuromorphic computation using oscillatory or alternative dynamics. In addition, those computational frameworks need to be matched to energy efficient neuromorphic hardware such as coupled superconducting oscillators (e.g. RSFQ - Rapid Single Flux Quantum devices).
The ideal candidate would be capable of creating novel ideas and frameworks for flexible analog computation, have experience with computation in dynamical systems and/or neuroscience, as well as exposure to neuromorphic hardware simulations and design. Postdoctoral researchers will have access to allocations on some of the world-leading supercomputers including Cori, and Perlmutter (Berkeley/NERSC).
What You Will Do:
- Processing in dynamically self-reconfiguring neuronal networks.
- Create novel ideas and frameworks for flexible analog computation.
- Coordination of large scale distributed computation as well as energy efficient neuromorphic hardware.
- Provide guidance for novel directions to develop frameworks for flexible neuromorphic computation using oscillatory or alternative dynamics.
- Match computational frameworks to energy efficient neuromorphic hardware such as coupled superconducting oscillators (e.g., RSFQ - Rapid Single Flux Quantum devices).
What is Required:
- PhD in Physics, Mathematics, Computer science, Computational Neuroscience or a related field.
- Demonstrated creativity, initiative and ability to design, develop and implement complex solutions in consultation with designated technical expert(s).
- Publish and present research results in journals and conference proceedings.
- Experience in either computational neuroscience or neuromorphic hardware.
- Ability to work productively both independently and as part of a diverse team.
Notes:
- 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.
- Salary will be predetermined based on postdoctoral step rates.
- This position may be 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.
- This position will be remote initially, but limited to individuals residing in the United States tentatively until 2021 due to COVID-19. Once the Bay Area shelter-in-place restrictions are lifted, work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
Equal Employment Opportunity:
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