Research Specialist B (Department of Neurosurgery)

Job Description Summary

We are seeking a highly motivated Research Specialist with experience in signal processing, machine learning, and intracranial EEG (iEEG) analysis to join our cutting-edge neuroscience research team. The successful candidate will play a key role in developing computational models and applying advanced techniques to analyze iEEG data, with the goal of identifying neural biomarkers related to brain function and neurological disorders.

Job Responsibilities:

• Develop and apply advanced signal processing techniques (e.g., Fourier Transform, wavelet analysis, filtering, etc.) to extract meaningful features from iEEG signals.
• Analyze spectral data from iEEG recordings to identify patterns and features associated with specific neural activities or clinical conditions.
• Build, train, and optimize machine learning models (supervised, unsupervised, deep learning) to detect and classify biomarkers from high-dimensional iEEG data.
• Identify potential biomarkers (e.g., power spectral density, phase coherence, connectivity metrics) from intracranial spectral data and validate their relevance for various neurological of psychiatric disorders.
• Work closely with neuroscientists, clinicians, and engineers to integrate data analysis pipelines with clinical trials and experimental protocols.
• Contribute to organizing, preprocessing, and managing large-scale iEEG datasets using best practices in data science, ensuring data integrity and reproducibility.

Qualifications

• Bachelor of Science and 1 to 3 years of experience or equivalent combination of education and experience is required.

Position is contingent upon continued funding.

Job Location - City, State

Philadelphia, Pennsylvania

Department / School

Perelman School of Medicine

Pay Range

$50,000.00 - $58,000.00 Annual Rate

Salary offers are made based on the candidate's qualifications, experience, skills, and education as they directly relate to the requirements of the position, and in alignment with salary ranges based on external market data for the job's level. Internal organization and peer data at Penn are also considered.