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Texas A&M University - College Station

Public university in College Station, TX

Postdoctoral Research Associate

Full-Stack EngineeringPosted on Nov 2
Full-timeHouston, TX, USANo salary listedIn-person

About the Job

Requirements

  • A Ph.D. or equivalent doctoral degree in Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Medical Physics, or a closely related quantitative discipline.
  • Complete human-subjects research (CITI) and MRI safety training within 30 days of hire.
  • Have experience developing, evaluating, or troubleshooting computational or engineering systems through doctoral research or equivalent advanced training.
  • Have scientific programming and quantitative data-analysis experience, demonstrated by first-author publications or equivalent work products.
  • Have advanced programming skills in Python, MATLAB, C/C++, or related languages.
  • Have strong knowledge of software engineering practices, including debugging, testing, version control, documentation, configuration management, and reproducibility.
  • Understand real-time systems concepts, including latency, synchronization, timing drift, buffering, dropped data, and failure recovery.
  • Have knowledge of Linux/Unix environments and shell scripting.
  • Be able to translate scientific and engineering requirements into computational solutions.
  • Have knowledge of data privacy and secure handling of human-subjects’ data.

Responsibilities

  • Optimize and maintain a real-time closed-loop fMRI neuromodulation platform.
  • Develop and modify software interfaces for fMRI-based real-time applications.
  • Improve graphical and user interfaces used for participant-facing neuromodulation displays.
  • Maintain and troubleshoot real-time pipelines for data acquisition, preprocessing, signal extraction, filtering (e.g., exponential moving average and Kalman), analysis, closed-loop output generation and real-time display updating, visualization, and logging.
  • Integrate software with imaging systems, workstations, networked data streams, displays, and experimental hardware. Develop timing, synchronization, queueing, latency, and overrun-management strategies to keep updates on schedule at each repetition time (TR).
  • Implement structured logging and diagnostic approaches to detect missed data, dropped samples, timing drift, and processing failures.
  • Apply the Papageorgiou Lab’s computational pipeline, such as signal processing, machine learning, dimensionality reduction, classification, state-space and hidden Markov modeling, and network-level analysis.
  • Develop validation and regression-testing procedures to confirm that the software continues to perform correctly after each change.
  • Support MRI scanning sessions with human participants.
  • Assist, mentor, collaborate with, and/or supervise student researchers, graduate students, and medical students working on research related to the project, as needed.
  • Collaborate with clinicians, neuroscientists, engineers, imaging scientists, and computational researchers.
  • Contribute to manuscripts, presentations, documentation, and grant-related research.
  • Prepare presentation materials on research topics for presentation to small and/or large groups.
  • Participate in preparing required technical progress reports to research sponsors.
  • Perform other duties as assigned.

Desired Qualifications

  • Three years of experience with real-time systems, hardware-software interfaces, or MRI/fMRI acquisition or analysis.
  • Knowledge of MRI neurofeedback, brain-computer interfaces, or closed-loop biomedical systems.
  • Experience with AFNI, FSL, SPM, Turbo-BrainVoyager, or related neuroimaging software.
  • Experience with Siemens real-time data export.
  • Knowledge of event-driven, asynchronous, multithreaded, or multiprocessing architectures.
  • Knowledge of real-time signal processing, network communication or inter-process communication, hardware triggering or instrumentation, GPU or parallel computing, machine learning, functional connectivity or network analysis, or research software used for human fMRI experiments.

About the Company

Texas A&M University - College Station

Public university in College Station, TX

Texas A&M University - College Station is the main campus of Texas A&M University in College Station, Texas. It provides undergraduate and graduate education and conducts research across a broad range of academic and professional fields.

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