Postdoctoral Research Associate, Real-Time fMRI Neuromodulation Engineering

The Papageorgiou Laboratory at the Texas A&M School of Engineering Medicine (EnMed) in Houston develops individualized, AI-guided, real-time fMRI neuromodulation technologies for precision neurorehabilitation, aiming 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.

The postdoctoral research associate will use computational, software and systems engineering expertise to advance the lab's closed-loop neuromodulation platform: real-time pipelines for acquisition, preprocessing, signal extraction, filtering (for example exponential moving average and Kalman filters), closed-loop output and display; software and hardware integration with imaging systems and networked data streams; timing, synchronisation and latency management at each repetition time; diagnostics, validation and regression testing; and the lab's computational methods, including machine learning, dimensionality reduction, state-space and hidden Markov modelling and network-level analysis.

The role spans electrical engineering, neuroengineering, computational neuroscience and biomedical imaging, includes support of MRI sessions with human participants and collaboration with clinicians, neuroscientists and imaging scientists, and contributes to manuscripts and grants.

PhD or equivalent in electrical, computer or biomedical engineering, computer science, medical physics or a closely related quantitative discipline; CITI human-subjects and MRI safety training within 30 days of hire. Preferred: three years of experience with real-time systems, hardware-software interfaces or MRI/fMRI acquisition or analysis; MRI neurofeedback, brain-computer interfaces or closed-loop biomedical systems; AFNI, FSL, SPM or Turbo-BrainVoyager; real-time signal processing, GPU or parallel computing and machine learning.