Postdoctoral Fellow in BCI/Neurology at UTHealth Neurosurgery & Rice University ECE

The Translational Biomimetic Bioelectronics Lab (TBBL) at UTHealth / Rice University is seeking a postdoctoral fellow to work on the development of brain-computer interfaces (BCIs) for treatment and rehabilitation of debilitating neurological disorders – ALS, paralysis, locked-in, and aphasia. The postdoctoral fellow will function as part of a multidisciplinary team of technologists, neurosurgeons, neurologists, and speech neuroscientists. We have two projects with openings: (1) BCI application of novel, patent-pending depth electrode array, and (2) developing a high-resolution epilepsy diagnostic tool. Broad neuroscience or neurology background is desired for
both.

The fellow will receive training for future opportunities in either academia or medical device industry. The successful candidate will work at the intersection of experimental neuroscience, computational neuroscience, and neuroelectronic to implement neurosurgical tools in preclinical models and in first-in-human experiments.

TBBL: Our mission is first-in-human demonstrations of the most advanced bioelectronics for the treatment of neurologic disease. Multiple Postdoctoral Fellow research positions are available in the TBBL at The University of Texas Health Science Center at Houston (UTHealth) (www.seymourlab.org). We are part of the newly formed Texas Institute for Restorative Neurotechnology’s (TIRN).

World Class Environment: Fellows will benefit from a close interaction with our collaborating experts in the fields of neurosurgery, neurology, neuroscience, machine learning, materials science, mixed-mode circuits, and system design. Our closest collaborators at UTHealth are neurosurgeons, neurologists, and neuroscientists who offer critical design input for human or primate use. Our lab is also located in the Biosciences Research Collaborative at Rice University and part the Rice Neuroengineering Initiative, thus collaborations are possible with faculty at UTHealth, Rice University, and Baylor College of Medicine. Our front-end fabrication is performed at the Rice Nanofab facility.

Responsibilities will include but may not be limited to:

• Experimental data collection and signal processing using novel electrophysiology tools
• Development of machine-learning algorithms to maximize the information capacity of our high-density arrays
• Integration of data collection and signal processing algorithms
•  Co-author applications for institutional review board (IRB) and investigational device exemption (IDE) approval
• Presentation of the results at the scientific meetings and publication of high impact journal articles
•  Participation in grant writing and preparation
• Mentoring of junior staff

Qualifications and Skills:

•  PhD in neuroscience, biomedical or electrical engineering, or related fields
• Experience with pre-clinical models including mice, rats, pigs or sheep
•  Experience in neural engineering, including BCIs, machine learning, neuroprosthetics
• Substantial experience with electrophysiology, including any of the following: single units, LFPs, ECoG, or EEG data analysis
• Experience in biomedical signal processing, feature extraction and machine learning applied to biological and/or neural datasets
• Programming skills (Python and/or MATLAB)
• Knowledge or strong interest in speech BCI and speech neuroscience
• Excellent verbal and written communication skills
• Strong publication record and academic credentials
• Ability to work effectively both independently and in collaboration with multiple principal investigators

Salary

• Competitive salary (typically above the minimum defined by the NIH guidelines), benefits, and moving expenses.

Deadline

• The positions are available immediately, and the applications are considered on an ongoing basis until the positions are filled.

How to Apply:

The application should be sent to Dr. John Seymour, john.p.seymour@uth.tmc.edu.

The application should include the candidate’s CV with the list of publications, a statement of interests, and the names and contact information of at least three professional references.

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