Postdoctoral Fellow-MSH-13400-374
About The Position
This new initiative is focused on using behavioral measures and computational methods to define novel clinical signatures that can be used for individual-level prediction and clinical decision making in treating mental disorders. This study, titled, “Phenotypes REimagined to Define Clinical Treatment and Outcome Research (PREDiCTOR)”, will use objective, scalable, and cost-effective measurements to define novel clinical signatures that can be used for individual-level prediction and clinical decision-making in treating mental health disorders. This pilot study will explore the safety, feasibility, clinical effects and mechanism of deep brain stimulation in the substantia nigra pars reticulata (SNr DBS) in 5 patients with treatment resistant schizophrenia. The pilot study will primarily investigate safety of the DBS surgical procedure and chronic stimulation, compliance with postsurgical care, follow-up DBS programing and research visits, and home-based procedures, including managing the DBS patient-controller and daily recordings of DBS sensing, symptom severity and audiovisual measures. Secondary outcomes are DBS related clinical changes, including hallucinations, delusions, negative symptoms and cognitive function, and optional intraoperative measures including acute symptom changes, electrophysiology, dopamine voltammetry, and brain biopsy.
Requirements
- M.D. or Ph.D. in Neuroscience, Medicine, Computer Science, Machine Learning, Data Science, Biomedical Informatics, Electrical Engineering, or a related field.
- Demonstrated experience in one or more of the following areas: computational psychiatry, machine learning, and AI.
- Proficiency in programming languages such as Python or MATLAB is highly desirable.
- Excellent data analysis skills and familiarity with methodologies used in biomedical research.
- Strong written and verbal communication skills, with a proven track record of research publications.
- 1-2 years of Research Experience
Responsibilities
- Conduct empirical studies in computational psychiatry, analyze multi-modal datasets, and synthesize insights to support hypothesis-driven research and evidence-based treatment strategies.
- Work collaboratively within an interdisciplinary team, and contribute to mentoring junior researchers, including graduate students and research assistants.
- Assist in recruiting and consenting patients with chronic schizophrenia that have previously failed to respond to antipsychotics including clozapine and are able to safely comply with a study involving brain surgery and management of an implanted device.
- Assist in collecting intraoperative data, pre-and postoperative MRI scans and follow-up recordings, and assist in patient device management.
- Assist in analyzing home-based audiovisual (face, speech) data that can be correlated with recordings of symptoms and brain sensing.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
