Associate Scientist

University of Miami•Miami, FL

1d•Onsite

About The Position

The University of Miami/UHealth department of Neurology has an exciting opportunity for a Full Time Associate Scientist to work at the UHealth Medical Campus. The Associate Scientist, SOM supports the University’s research goals and objectives by performing laboratory experiments in his/her areas of interest, expertise, or assignment. Moreover, the incumbent performs various analytical procedures involving method development and application development and synthesis. The Associate Research Scientist will serve as a key independent contributor within the Hacking Consciousness Lab, leading the design, implementation, and analysis of advanced neurophysiologic and multimodal biomarker studies in acute disorders of consciousness. The individual will oversee complex EEG signal processing pipelines, integrate multimodal datasets (EEG, autonomic, eye-tracking, and imaging), and contribute to the development of translational tools for detection and prognostication of covert consciousness in critically ill patients. This role requires a high degree of scientific independence, including leading methodological innovation, mentoring junior trainees, contributing to grant writing, and driving first- and senior-author publications. The Associate Research Scientist will collaborate across institutions and play a central role in advancing NIH-funded projects and emerging translational applications.

Requirements

Doctorate degree - Philosophy (PhD) Neuroscience, Biomedical Engineering, Data Science, computer science or related quantitative field.
Minimum 5 years of relevant experience.
Advanced programming skills (Python, MATLAB) with experience in neurophysiology toolboxes (e.g., MNE).
Strong expertise in EEG analysis, including ERPs, spectral methods, and connectivity metrics.
Experience with machine learning and statistical modeling techniques.
Ability to independently design analyses and interpret complex datasets.
Strong scientific writing skills with ability to lead manuscripts and contribute to grants.
Collaborative mindset with ability to work across clinical and engineering teams.
Mentorship ability and commitment to training junior researchers.
High level of organization and ability to manage multiple projects simultaneously.
Interest in translational neuroscience and development of bedside diagnostic tools.

Nice To Haves

Postdoctoral or equivalent research experience.
Demonstrated expertise in EEG signal processing and/or neurophysiologic data analysis.
Track record of peer-reviewed publications, including first-author contributions.
Experience with multimodal datasets and machine learning approaches.
Prior involvement in NIH-funded or large collaborative research projects.

Responsibilities

Contributes to basic and applied research activities including authorship of scientific publications, technical and agency reports, and patent preparations.
Publishes in refereed journals in collaboration with department leadership or independently.
Supervises research employees and non-exempt staff.
Writes extramural proposals with approval of senior managing staff.
Creates and conducts experiments and analyzes results.
Works with other researchers to use and develop end products.
Provides ready access to all experimental data for the faculty researchers, supervisors, and other relevant staff.
Requests or acquires equipment and supplies for assigned project(s).
Applies for grants to continue research and prepares materials for submission to granting agencies and foundations.
Adheres to University and unit-level policies and procedures and safeguards University assets.
Lead the development and optimization of advanced EEG analysis pipelines, including time-frequency analysis, TRF modeling, ERP analysis, and machine learning approaches for neural signal classification.
Design and implement multimodal data integration frameworks combining EEG, autonomic (EDA/GSR), eye-tracking, and neuroimaging (DTI) data.
Independently conduct statistical analyses, including mixed-effects modeling, classification models, and predictive analytics for clinical outcomes.
Contribute to study design for NIH-funded and industry-sponsored research projects, including protocol development and analytic planning.
Lead and co-author high-impact manuscripts; contribute to grant writing (R21, R01, DoD, and foundation grants).
Mentor trainees (students, residents, fellows) in data analysis, coding, and research methodology.
Collaborate with multi-institutional partners to ensure protocol fidelity and reproducibility across sites.
Develop and maintain scalable, reproducible data pipelines using Python/MATLAB and relevant neuroinformatics tools (e.g., MNE, machine learning frameworks).
Participate in translation of research tools into clinically deployable platforms (e.g., mobile applications, bedside diagnostics).
Present research findings at national and international conferences.