Postdoctoral Research Associate - Tennessee (TN)

Only for registered members Tennessee (TN), United States

2 days ago

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$52,000 - $85,000 (USD) per year *
* This salary range is an estimation made by beBee
Requisition Id 15682  · Overview: · We are 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, and machi ...
Job description

Requisition Id 15682 

Overview:

We are 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, and machine learning for edge processing.

The successful candidate will work with a multi-institutional and multi-disciplinary team to develop AI-enabled, low-latency signal-processing algorithms for next-generation pixel detectors used in high-energy physics experiments.

This position offers the opportunity to engage in cutting-edge research spanning detector simulation, Spiking Neural Network (SNN) design, neuromorphic hardware, and data-rich experimental systems such as CMS pixel detectors, Timepix4, and novel photodetector technologies.

This position resides in the Relativistic Nuclear and High Energy Physics group in the Physics Division, Physical Science Directorate, at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities:

Depending on background and interest, responsibilities may include:

Neuromorphic & ML Algorithm Development:

  • Development and training of Spiking Neural Networks (SNNs) for clustering, classification, and interpolation of pixel detector data.
  • Exploration of spike-based data encoding/decoding strategies.
  • Hyperparameter optimization using advanced computing resources (e.g., HPC clusters).
  • Detector Simulation & Data Processing:

  • Use and extension of Allpix2 and TCAD-based simulation tools.
  • Generation of large simulation datasets for algorithm training and validation.
  • Integration of simulation with neuromorphic platforms.
  • FPGA / Hardware-Embedded AI:

  • Deployment of SNNs to FPGA-based neuromorphic hardware (e.g., NeuroSpike/NeuroSpark).
  • RTL generation using HLS workflows and evaluation of resource usage, latency, and performance.
  • Participation in hardware test benches for real detector systems.
  • Experimental Detector Work:

  • Testing and characterization of pixel detectors (CMS HL-LHC, Timepix4, AC-LGAD, PDCs).
  • On-sensor data processing demonstration with hardware prototypes.
  • Potential involvement in beam tests or radiation-source laboratory setups.
  • Basic Qualifications:

  • 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++.
  • Preferred Qualifications:

  • Ability to work collaboratively in a multidisciplinary team.
  • Strong communication skills and the ability to document and present research clearly.
  • 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 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.

    Letters of Recommendation:

    Please submit three letters of reference when applying for this position. You can upload these directly to your application or have them sent to  with the position title and number referenced in the subject line.

    Instructions to upload documents to your candidate profile:

  • Login to your account via
  • View Profile
  • Under the My Documents section, select Add a Document
  • Security, Credentialing, and Eligibility Requirements:

  • This position requires the ability to obtain and maintain an HSPD-12 PIV badge.
  • 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.
  • For foreign national candidates:

  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment.
  • Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
  • 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.

    If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: 

    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.

    We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

    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.



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