Important Info
Please send your application to fbaumer@stanford.edu, cc: Brenda2@stanford.edu with the subject line "LGS Postdoctoral Fellow Application - [Your Name]". We encourage applications from diverse candidates and are committed to creating an inclusive environment for all employees.
Electrophysiology and MRI Data Analysis of Patients with Lennox-Gastaut Syndrome
About Us: Stanford Pediatric Epilepsy Research is at the forefront of research in neuroscience, focusing on understanding complex neurological disorders. We are seeking a highly motivated postdoctoral fellow to join our team dedicated to investigating the brain changes associated with Lennox-Gastaut Syndrome (LGS) through advanced data analysis techniques.
About Lennox-Gastaut Syndrome: Lenox-Gastaut Syndrome is a severe form of epilepsy that often involves a combination of multiple seizure types, resulting in significant cognitive and developmental challenges. Research in this area is critical for developing targeted therapies and improving patient outcomes.
Position Overview: The selected candidate will be responsible for analyzing large datasets from electrophysiology and MRI studies. The goal is to identify and characterize brain changes associated with LGS, aiming to contribute to better understanding and treatment options for this syndrome. This role presents an exciting opportunity to work in a collaborative environment with leading researchers in the field.
Key Responsibilities:
Conduct analysis of large-scale electrophysiology (intracranial and scalp EEG) and MRI data sets.
Develop and implement algorithms for data processing and interpretation.
Collaborate with clinicians and researchers to design studies and analyze results.
Present findings to both scientific and non-scientific audiences.
Contribute to writing research papers and grant proposals.
Train and mentor students and research assistants as needed.
- PhD in Neuroscience, Biomedical Engineering, Computational Biology, or a related field.
- Strong background in signal processing, including neuroimaging and/or electrophysiology (EEG, MEG) data analysis.
- Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred.
- Demonstrated experience with large dataset management and analysis.
- Excellent problem-solving skills and ability to work independently as well as collaboratively.
- Strong communication skills, both written and verbal.
Preferred Qualifications:
- Experience combining large clinical and research data sets.
- Interested and comfortable working with pediatric patients with special needs.
- A track record of publications in relevant fields.
- A cover letter outlining research interests and relevant experience.
- A current CV.
- Contact information for three references.