Postdoctoral Research Associate

Texas A&M University System • Houston, TX

7d • Onsite

About The Position

The Papageorgiou Laboratory at the Texas A&M School of Engineering Medicine develops individualized, AI-guided, real-time fMRI neuromodulation technologies for precision neurorehabilitation. Its goal is to restore sensorimotor and cognitive function in patients affected by cancer treatment, neurologic injury, and neurodegenerative disease by translating each patient’s anatomical and functional brain network into closed-loop interventions that adapt in real time.

Under general supervision, the Postdoctoral Research Associate conducts research in their field of expertise and applies advanced computational, software engineering, and systems engineering expertise to advance an existing closed-loop iNM platform. The work spans computational architecture, software interfaces, real-time data processing, visualization, hardware-software integration, system reliability, and performance monitoring, integrating electrical engineering, neuroengineering, computational neuroscience, and biomedical imaging.

Requirements

• 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.
• 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 and collaborate effectively within a multidisciplinary team.
• Knowledge of data privacy and secure handling of human-subjects’ data.
• Attention to detail.

Nice To Haves

• Three years of experience with real-time systems, hardware-software interfaces, and 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, demonstrated through first-author publications or equivalent work products.
• Demonstrated self-motivation, independent problem-solving, and sustained commitment to complex projects.
• Knowledge of MRI neurofeedback, brain-computer interfaces, or closed-loop biomedical systems.
• Knowledge of AFNI, FSL, SPM, Turbo-BrainVoyager, or related neuroimaging software.
• Knowledge of 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, and research software used for human fMRI experiments.

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, 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 the laboratory’s computational pipeline, including 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 continues to perform correctly after changes.
• Support MRI scanning sessions with human participants.
• May assist, mentor, collaborate with, and/or supervise student researchers, graduate students, and medical students working on research related to the project.
• Collaborate with clinicians, neuroscientists, engineers, imaging scientists, and computational researchers.
• Contribute to manuscripts, presentations, documentation, and grant-related research.
• Prepare presentation materials on the research topic for small and/or large groups.
• Participate in preparing required technical progress reports to research sponsors.
• Perform other duties as assigned.

Benefits

• Medical, prescription drug, dental, vision, life and AD&D, flexible spending accounts, and long-term disability insurance; Texas A&M contributes to employee health and basic life premiums.
• 12–15 days of annual paid holidays.
• Up to eight hours of paid sick leave and at least eight hours of paid vacation each month.
• Automatic enrollment in the Teacher Retirement System of Texas.
• Free exercise programs and release time for health and wellness.
• Free LinkedIn Learning training, webinars, and limited financial support to attend conferences, workshops, and more.
• Educational release time and tuition assistance for completing a degree while a Texas A&M employee.
• Living Well employee program.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree