Postdoctoral Research Associate - Neuromorphic Computing

UT-Battelle; Oak Ridge (TN); On-site; USD 60,000 - 80,000; Full time

Benefits offered by this job

Relocation Assistance

On-site amenities

Flexible work hours

Job summary

UT-Battelle's Oak Ridge National Laboratory is seeking a postdoctoral researcher to advance spiking neural networks on edge platforms. You will perform impactful research and apply methods across science and engineering domains.

You will develop low-level software and firmware for SNNs, evaluate hardware-software co-design approaches, and publish results in peer-reviewed venues. Collaborate with global experts, present at conferences, and contribute to education and outreach while advancing

Qualifications

• Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or closely related field.
• Strong programming proficiency in C, C++, and Python.
• Hands-on experience with embedded systems programming, bare-metal development, or RTOS (FreeRTOS/Zephyr).
• Experience with ARM/RISC-V microcontrollers and FPGA development using Verilog/VHDL/SystemVerilog.
• Proficiency with hardware communication protocols (SPI, I2C, UART, PCIe).
• Experience in software engineering: version control, documentation, tutorials.
• Solid understanding of neuromorphic computing and SNNs, neuron models, and training/conversion methods.
• Strong publication record in peer-reviewed venues.
• Excellent written and oral communication skills.
• Ability to work independently and in collaborative teams.

Responsibilities

• Research, develop, and optimize low-level software, drivers, and firmware for SNNs on embedded platforms.
• Research, develop, and evaluate hardware-software co-design for edge neuromorphic systems.
• Implement and validate SNN execution frameworks on ARM/RISC-V MCUs, FPGAs, or neuromorphic processors.
• Conduct power profiling, energy-per-inference measurements, and latency benchmarking on edge hardware.
• Build collaborations within ORNL and the neuromorphic communities worldwide.
• Publish research in high-impact journals and conferences.
• Author technical papers, reports, and proposals for internal/external release.
• Represent ORNL/Learning Systems Group with talks at conferences and workshops.

Skills

C/C++ programming

Python

Embedded systems programming

RTOS (FreeRTOS/Zephyr)

Verilog/VHDL/SystemVerilog

Git/version control

Publications or research communication

Education

Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or related field

Tools

FreeRTOS

Zephyr

Verilog

VHDL

SystemVerilog

ARM

RISC-V

FPGA

Vivado

Quartus

Git

LaTeX

Job description

Overview

As a postdoctoral researcher, you will help solve some of the most challenging problems the world faces. You will perform impactful research on a range of significant problems, and you will apply your work in multidisciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and hardware-software co-design skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, and disseminate innovative results through publications and presentations.

The Learning Systems Group at Oak Ridge National Laboratory advances the next generation of artificial intelligence by co-designing algorithms and computing systems to address complex challenges in science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging from edge sensors and neuromorphic systems to national supercomputers and quantum computers. Our work includes scientific knowledge discovery, autonomous and energy-efficient systems, threat intelligence and data fusion, agent-based modeling and digital twins, and predictive analysis for environmental and health applications. We are committed to recruiting and retaining highly motivated, creative researchers, postdoctoral fellows, and students who will help develop intelligent systems that learn, reason, and operate effectively across diverse computing environments.

Major Duties/Responsibilities

• Research, develop, and optimize novel low-level software, drivers, and firmware for executing SNNs on resource-constrained embedded platforms.
• Research, develop, and evaluate hardware-software co-design approaches for edge neuromorphic systems and event-driven processing architectures.
• Implement and validate spiking neural network (SNN) execution frameworks on microcontrollers (ARM, RISC-V), FPGAs, or specialized neuromorphic processors.
• Conduct power profiling, energy-per-inference measurements, and latency benchmarking on physical edge hardware platforms.
• Build strong collaborations within ORNL and with the neuromorphic computing and embedded systems communities worldwide.
• Publish research in high-impact journals and conferences.
• Author peer-reviewed papers, technical papers, reports, and proposals for internal and external release.
• Represent ORNL and the Learning Systems Group by giving talks at public forums (conferences, workshops, guest lectures, etc.).

Basic Requirements

• Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or a closely related field.
• Strong programming proficiency in C, C++, and Python.
• Hands-on experience with embedded systems programming, bare-metal development, or Real-Time Operating Systems (RTOS such as FreeRTOS or Zephyr).
• Experience with hardware development tools and microcontrollers based on ARM or RISC-V architectures, and with FPGA development using Hardware Description Languages (Verilog, VHDL, or SystemVerilog).
• Experience with standard hardware communication protocols (e.g., SPI, I2C, UART, PCIe).
• Experience in software engineering, including writing efficient, scalable software, using version control tools such as Git, maintaining software, writing software documentation, and creating tutorials explaining how to use the software.
• Solid understanding of neuromorphic computing and SNNs, including common neuron models (e.g., leaky integrate-and-fire) and SNN training or conversion methods (e.g., spike-timing-dependent plasticity (STDP), surrogate-gradient learning or ANN-to-SNN conversion).
• A strong publication record in peer-reviewed journals and conferences demonstrating sound embedded hardware/software or computational research.
• Excellent written and oral communication skills.
• Ability to work independently and to participate creatively in collaborative teams across the laboratory.
• Ability to set priorities to accomplish multiple tasks within deadlines and adapt to changing needs.

Preferred Qualifications

• Experience with physical power profiling tools, oscilloscopes, and logic analyzers for hardware energy benchmarking.
• Experience interfacing neuromorphic hardware or SNNs with event-based vision sensors (DVS), edge sensors, or robotics platforms.
• Familiarity with event-driven hardware interfaces and protocols, such as Address-Event Representation (AER).
• Experience with hardware-aware AI optimization, including quantization, pruning, fixed-point arithmetic, and memory-footprint reduction for microcontrollers.
• Familiarity with neuromorphic software frameworks (e.g., SuperNeuro, NEST, Brian2, BindsNET, or snnTorch).
• Knowledge of emerging non-volatile memory devices (e.g., memristors, spintronics) or custom ASIC testbeds.
• Hands-on experience with commercial or research neuromorphic hardware platforms, such as ORNL's NeuroCoreX.
• Experience with FPGA design flows (e.g., AMD/Xilinx Vivado or Intel Quartus) and High-Level Synthesis (e.g., Vitis HLS).
• Experience using LaTeX for writing scientific manuscripts.

Special Requirements

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

• For employment at Oak Ridge National Laboratory (ORNL), a Real-ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation
• To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
• Visa sponsorship is not available for this position.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.