equanimous
Norse clairvoyant shapeshifter goddess
Your research isI see our friends at Intellisense looking for someone to assist with NN on neuromorphic processors.
Presume to also assist with the awarded Ph II NECR project which we know about and possibly the Ph I ADORBL project.
Land your dream job with HiCounselor
HiCounselor combines technology to get you more job interviews with instructors from top companies to help you ace those interviews and land your dream jobhicounselor.com
Senior Software Engineer
Company: Intellisense Systems Inc
Location: Torrance, California, United States
Posted on: January 01
Intellisense Systems innovates what seemed impossible. We are a fast-growing Southern California technology innovator that solves tough, mission-critical challenges for our customers in advanced military, law enforcement, and commercial markets. We design, develop, and manufacture novel technology solutions for ground, vehicle, maritime, and airborne applications. Our products have been deployed in every extreme environment on Earth!
We are looking for an exceptional Senior Software Engineer to join our Artificial Intelligence (AI) and Radio Frequency (RF) Systems team. The team works on cutting-edge technologies for government customers and DoD applications.
As part of the team, you will work alongside other experienced scientists and engineers to develop novel cutting-edge solutions to several challenging problems. From creating experiments and prototyping implementations to designing new machine learning algorithms, you will contribute to algorithmic and system modeling and simulation, transition your developments to software and hardware implementations, and test your integrated solutions in accordance with project objectives, requirements, and schedules.
Projects You May Work On:
- Real-time object detection, classification, and tracking
- RF signal detection, classification, tracking, and identification
- Fully integrated object detection systems featuring edge processing of modern deep learning algorithms
- Optimization of cutting-edge neural network architectures for deployment on neuromorphic processors
Neuromorphic Enhanced Cognitive Radio | SBIR.gov
www.ussbir.io
Neuromorphic Enhanced Cognitive Radio
Award Information
Agency:National Aeronautics and Space Administration
Branch:N/A
Contract:80NSSC22CA063
Agency Tracking Number:211743
Amount:$799,985.00
Phase: Phase II
Program:SBIR
Solicitation Topic Code:H6
Solicitation Number:SBIR_21_P2
Timeline
Solicitation Year:2021
Award Year:2022
Award Start Date (Proposal Award Date):2022-05-25
Award End Date (Contract End Date):2024-05-24
Intellisense Systems, Inc. proposes in Phase II to advance development of a Neuromorphic Enhanced Cognitive Radio (NECR) device to enable autonomous space operations on platforms constrained by size, weight, and power (SWaP). NECR is a low-size, -weight, and -power (-SWaP) cognitive radio built on the open-source framework, i.e., GNU Radio and RFNoCtrade;, with new enhancements in environment learning and improvements in transmission quality and data processing. Due to the high efficiency of spiking neural networks and their low-latency, energy-efficient implementation on neuromorphic computing hardware, NECR can be integrated into SWaP-constrained platforms in spacecraft and robotics, to provide reliable communication in unknown and uncharacterized space environments such as the Moon and Mars. In Phase II, Intellisense will improve the NECR system for cognitive communication capabilities accelerated by neuromorphic hardware. We will refine the overall NECR system architecture to achieve cognitive communication capabilities accelerated by neuromorphic hardware, on which a special focus will be the mapping, optimization, and implementation of smart sensing algorithms on the neuromorphic hardware. The Phase II smart sensing algorithm library will include Kalman filter, Carrier Frequency Offset estimation, symbol rate estimation, energy detection- and matched filter-based spectrum sensing, signal-to-noise ratio estimation, and automatic modulation identification. These algorithms will be implemented on COTS neuromorphic computing hardware such as Akida processor from BrainChip, and then integrated with radio frequency modules and radiation-hardened packaging into a Phase II prototype. At the end of Phase II, the prototype will be delivered to NASA for testing and evaluation, along with a plan describing a path to meeting fault and tolerance requirements for mission deployment and API documents for integration with CubeSat, SmallSat, and rover for flight demonstration.
Adaptive Deep Onboard Reinforcement Bidirectional Learning System
Award Information
Agency:National Aeronautics and Space Administration
Branch:N/A
Contract:80NSSC22PB053
Agency Tracking Number:221780
Amount:$149,996.00
Phase: Phase I
Program:SBIR
Solicitation Topic Code:H6
Solicitation Number:SBIR_22_P1
Timeline
Solicitation Year:2022
Award Year:2022
Award Start Date (Proposal Award Date):2022-07-22
Award End Date (Contract End Date):2023-01-25
NASA is seeking innovative neuromorphic processing methods and tools to enable autonomous space operations on platforms constrained by size, weight, and power (SWaP). To address this need, Intellisense Systems, Inc. (Intellisense) proposes to develop an Adaptive Deep Onboard Reinforcement Bidirectional Learning (ADORBL) processor based on neuromorphic processing and its efficient implementation on neuromorphic computing hardware. Neuromorphic processors are a key enabler to the cognitive radio and image processing system architecture, which play a larger role in mitigating complexity and reducing autonomous operations costs as communications and control become complex. ADORBL is a low-SWaP neuromorphic processing solution consisting of multispectral and/or synthetic aperture radar (SAR) data acquisition and an onboard computer running the neural network algorithms. The implementation of artificial intelligence and machine learning enables ADORBL to choose processing configurations and adjust for impairments and failures. Due to its speed, energy efficiency, and higher performance for processing, ADORBL processes raw images, finds potential targets and thus allows for autonomous missions and can easily integrate into SWaP-constrained platforms in spacecraft and robotics to support NASA missions to establish a lunar presence, to visit asteroids, and to extend human reach to Mars. In Phase I, we will develop the CONOPS and key algorithms, integrate a Phase I ADORBL processing prototype to demonstrate its feasibility, and develop a Phase II plan with a path forward. In Phase II, ADORBL will be further matured, implemented on available commercial neuromorphic computing chips, and then integrated into a Phase II working prototype along with documentation and tools necessary for NASA to use the product and modify and use the software. The Phase II prototype will be tested and delivered to NASA to demonstrate for applications to CubeSat, SmallSat, and rover flights.
Must be