Postdoctoral Research Associate

Our Commitment

Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing varying opinions and perspectives strengthens our core values which are: Respect, Excellence, Leadership, Loyalty, Integrity, and Selfless Service.

Who we are

As one of the fastest-growing academic health centers in the nation, Texas A&M Health encompasses five colleges and numerous centers and institutes working together to improve health through transformative education, innovative research and team-based health care delivery.

What we want
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. The laboratory's 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 (neurofunctional twin) into closed-loop interventions that adapt in real time.

The Postdoctoral Research Associate, under general supervision, is responsible for conducting research into their field of expertise. The Postdoctoral Research Associate will utilize their advanced computational, software engineering, and systems engineering expertise to advance an existing 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.

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, 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.

• May assist, mentor, collaborate, and/or supervise student researchers and/or graduate students and/or medical students, who are 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 research topic that may be presented to small and/or large groups.
• Actively participate in the preparation of required technical progress reports to research sponsors.
• Other duties as assigned

Qualifications:

• Ph.D. or equivalent doctoral degree iin Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Medical Physics, or a closely related quantitative discipline.

• Completion of human-subjects research (CITI) and MRI safety training is required within 30 days of hire.

• 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

• 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

Why Texas A&M University?   

We are a prestigious university with strong traditions, Core Values, and a community of caring and collaboration. 

• Medical, prescription drug, dental, vision, life and AD&D, flexible spending accounts, and long-term disability insurance with Texas A&M contributing 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 

• Health and Wellness: Free exercise programs and release time  

• Professional Development: All employees have access to 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, a program at Texas A&M that has been built by employees, for employees 

Instructions to Applicants: Applications received by Texas A&M University must either have all job application data entered, or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to pre-populate the online application.

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.

Equal Opportunity/Veterans/Disability Employer.