Postdoctoral Research Associate

About the Role

The Papageorgiou Laboratory at the Texas A&M School of Engineering Medicine (EnMed) develops individualized, AI-guided, real-time fMRI neuromodulation (iNM) technologies for precision neurorehabilitation. This role involves conducting research, utilizing advanced computational, software engineering, and systems engineering expertise to advance a closed-loop iNM platform. The work covers computational architecture, software interfaces, real-time data processing, visualization, hardware-software integration, system reliability, and performance monitoring. This role integrates electrical engineering, neuroengineering, computational neuroscience, and biomedical imaging.

Key Responsibilities

• Research/Data Analysis
• 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 for participant-facing neuromodulation displays.
• Maintain and troubleshoot real-time pipelines for data acquisition, preprocessing, signal extraction, filtering (e.g., exponential moving average, Kalman), analysis, closed-loop output generation, 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 computational pipelines, 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 software performance.
• Support MRI scanning sessions with human participants.
• Training/Laboratory Coordination
• May assist, mentor, collaborate, and/or supervise student researchers, graduate students, and/or medical students.
• 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.
• Actively participate in the preparation of required technical progress reports to research sponsors.
• Other duties as assigned.

Requirements & Tech Stack

• Required Education
• Ph.D. or equivalent doctoral degree in Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Medical Physics, or a closely related quantitative discipline.
• Required Licenses And Certifications
• Completion of human-subjects research (CITI) and MRI safety training is required within 30 days of hire.
• Knowledge, Skills, And Abilities
• Advanced programming skills in Python, MATLAB, C/C++, or related languages.
• Strong knowledge of software engineering practices including debugging, testing, version control, documentation, configuration management, and reproducibility.
• Understanding of real-time systems concepts including latency, synchronization, timing drift, buffering, dropped data, and failure recovery.
• Knowledge of Linux/Unix environments and shell scripting.
• Strong quantitative reasoning, troubleshooting, and problem-solving skills.
• Ability to translate scientific and engineering requirements into computational solutions.
• Ability to work independently while collaborating effectively within a multidisciplinary team.
• Knowledge of data privacy and secure handling of human-subjects’ data.
• Attention to detail.

Preferred Qualifications

• Three years of experience with real-time systems; hardware-software interfaces; MRI/fMRI acquisition or analysis.
• Experience developing, evaluating, or troubleshooting computational or engineering systems through doctoral research or equivalent advanced training.
• Experience with scientific programming and quantitative data analysis, shown by first-author publications or equivalent work products.
• A demonstrated record of self-motivation, independent problem-solving, and sustained commitment to complex projects.
• Knowledge of: MRI neurofeedback, brain-computer interfaces, or closed-loop biomedical systems; AFNI, FSL, SPM, Turbo-BrainVoyager, or related neuroimaging software; Siemens real-time data export; event-driven, asynchronous, multithreaded, multiprocessing architectures; 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; and research software used for human fMRI experiments.