Location: Oak Ridge, TN, US, 37830
Company: Oak Ridge National Laboratory (ORNL)
Requisition ID: 15682
Oak Ridge National Laboratory (ORNL) is seeking a highly motivated Postdoctoral Research Associate to contribute to the NEUROPIX project, an interdisciplinary effort at the intersection of:
High-energy physics (HEP) detectors
Neuromorphic computing
FPGA/ASIC design
Machine learning for edge processing
The successful candidate will work with a multi-institutional, multidisciplinary team to develop AI-enabled, low-latency signal-processing algorithms for next-generation pixel detectors used in high-energy physics experiments.
This position resides in the Relativistic Nuclear and High Energy Physics group, Physics Division, Physical Science Directorate, at ORNL.
Neuromorphic & Machine Learning Algorithm Development:
Develop and train Spiking Neural Networks (SNNs) for clustering, classification, and interpolation of pixel detector data
Explore spike-based data encoding/decoding strategies
Perform hyperparameter optimization using HPC resources
Detector Simulation & Data Processing:
Use and extend Allpix2 and TCAD-based simulation tools
Generate large simulation datasets for algorithm training and validation
Integrate simulation with neuromorphic platforms
FPGA / Hardware-Embedded AI:
Deploy SNNs to FPGA-based neuromorphic hardware (NeuroSpike/NeuroSpark)
Generate RTL using HLS workflows; evaluate resource usage, latency, and performance
Participate in hardware test benches for real detector systems
Experimental Detector Work:
Test and characterize pixel detectors (CMS HL-LHC, Timepix4, AC-LGAD, PDCs)
Demonstrate on-sensor data processing with hardware prototypes
Potential involvement in beam tests or radiation-source laboratory setups
Ph.D. in Physics, Electrical Engineering, Computer Science, or a closely related field
Experience in at least one of the following areas:
FPGA programming (VHDL/Verilog, HLS)
Pixel detectors in high-energy physics or radiation detection
Neuromorphic computing or Spiking Neural Networks
Machine learning, AI/ML algorithms, or scientific computing
Strong programming skills in Python and/or C++
Ability to work collaboratively in a multidisciplinary team
Strong communication skills for clear documentation and presentation of research
Experience with:
Allpix2, GEANT4, detector simulation, or TCAD
FPGA toolchains (Xilinx Vitis/Vivado, Intel Quartus, HLS tools)
HPC environments or GPU-accelerated computing
On-detector firmware or data acquisition systems
Familiarity with HEP data formats and reconstruction
Background in semiconductor sensor physics or microelectronics
Applicants cannot have received their Ph.D. more than five years prior to the application date
Must complete all degree requirements before starting
Appointment length: up to 24 months with potential extension, contingent on performance and funding
Three letters required
Upload directly to the application or email postdocrecruitment@ornl.gov with the position title and number referenced
Position requires ability to obtain and maintain HSPD-12 PIV badge
Real ID-compliant identification required for employment
Must complete and pass a Federal Tier 1 background check
Foreign nationals: candidates without 3 consecutive years U.S. residency require Local Site Specific Only (LSSO) risk determination
U.S. Department of Energy (DOE) Office of Science national laboratory
80-year legacy addressing national scientific challenges
Team of 7,000+ employees
Environment valuing diverse perspectives and backgrounds
Competitive pay and benefits, including:
Medical, dental, and vision plans
401(k) and contributory pension plans
Life and disability insurance
Generous vacation, holidays, and parental leave
Legal insurance, identity theft protection, and educational assistance
On-site amenities: fitness, banking, cafeteria
Relocation assistance and employee discounts
Position open for a minimum of 5 days; closes when qualified candidate is identified
File types accepted: Word (.doc/.docx), Adobe PDF, RTF, HTML (.htm/.html), up to 5MB
Third-party resumes not accepted
Accommodation: For difficulty using the online application system or disability-related accommodations, email ORNLRecruiting@ornl.gov
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.