Postdoctoral Fellow-MSH-13400-374

Mount Sinai Morningside; New York (NY); On-site; USD 74,692 - 82,740; Full time

Job summary

Mount Sinai Morningside in New York City invites applications for a research-focused role within the PREDiCTOR initiative. The project combines behavioral measures and computational methods to define clinical signatures for individualized treatment and outcome prediction in mental health disorders.

The pilot study examines safety and mechanisms of deep brain stimulation in the SNr for patients with treatment-resistant schizophrenia, including DBS programming, postoperative care, and home-based

Qualifications

• Education in a relevant field (MD/PhD or equivalent).
• 1-2 years of research experience in neuroscience or computational psychiatry.
• Proficiency in Python or MATLAB.
• Strong data analysis skills and familiarity with biomedical research methods.
• Excellent written and verbal communication with publications.

Responsibilities

• Contribute to empirical studies in computational psychiatry and data synthesis.
• Collaborate in an interdisciplinary team and mentor junior researchers.
• Assist in recruiting patients with treatment-resistant schizophrenia and consent procedures.
• Collect intraoperative data, pre- and postoperative MRI scans and follow-up recordings; manage patient devices.
• Analyze home-based audiovisual data and correlate with brain sensing and symptoms.

Skills

Python

MATLAB

Machine learning

Data analysis

Education

MD/PhD in Neuroscience or related field

Job description

Description

Salary: $74,692-$82,740

Department: Psychiatry

Physical work location: 100 E 104th Street, 4th Floor, New York, NY 10029 and 521 W 57th St 6th Floor, New York, NY 10019

Name PI or Supervisor: Dr. Martijn Figee & Dr. Shalaila Haas

Responsibilities

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. The 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 programming 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.

Qualifications

• Conduct empirical studies in computational psychiatry, analyze multi-modal datasets, and synthesize insights to support hypothesis-driven research and evidence-based treatment strategies.
• Collaborate 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.

Education: M.D. or Ph.D. in Neuroscience, Medicine, Computer Science, Machine Learning, Data Science, Biomedical Informatics, Electrical Engineering, or a related field.

• Research Background: Demonstrated experience in one or more of the following areas: computational psychiatry, machine learning, and AI.
• Technical Skills: Proficiency in programming languages such as Python or MATLAB is highly desirable.
• Analytical Abilities: Excellent data analysis skills and familiarity with methodologies used in biomedical research.
• Communication Skills: Strong written and verbal communication skills, with a proven track record of research publications.

Experience Required: 1-2 years of Research Experience.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported.

Compensation

The salary range for the role is $72,500 - $80,000 annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses, incentive, differential pay or other forms of compensation or benefits.