Posted on Wed, 09/25/2024 - 12:02

Important Info

Faculty Sponsor (Last, First Name): 
Hernandez-Boussard, Tina
Other Mentor(s) if Applicable: 
Yair Bannett, MD
Stanford Departments and Centers: 
Med: Biomedical Informatics Research (BMIR)
Ped: Developmental Behavioral
Postdoc Appointment Term: 
A postdoc term is usually 2 years, though this may vary.
Appointment Start Date: 
Funding for this position is available and applications are reviewed on a rolling basis.
Group or Departmental Website: 
https://med.stanford.edu/boussard-lab.html
https://med.stanford.edu/profiles/yair-bannett
How to Submit Application Materials: 

To begin the application process, please send an email using the subject line “Postdoctoral Position in Machine Learning for Advancing Mental Health” to Tina Hernandez-Boussard, PhD at boussard AT stanford DOT edu, and include all required application materials.

If you have general questions, please contact the Boussard Lab Program Manager David L. M. Preston, MA, MBA, preston AT stanford DOT edu.

Does this position pay above the required minimum?: 
No. The expected base pay for this position is the Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY25 minimum is $73,800.

The Boussard Lab in the Division of Biomedical Informatics (BMIR), in the Department of Medicine at Stanford University, in collaboration with the Advanced Informatics for Mental Health lab of Yair Bannett, MD, MS, in the Department of Pediatrics, is seeking a highly motivated, passionate postdoctoral scholar looking to make an impact in the field of mental health, leveraging informatics to tackle real world problems.

Candidates are welcome from a variety of inter-related backgrounds such as biomedical informatics, computer science, electrical engineering, mental health services research/health policy, and/or biostatistics. Applications should be both independent thinkers and willing learners, both ambitious and team players, have a strong research publication record, and high-level understanding of programming and computer modeling.

This postdoc position offers a motivated researcher an opportunity to contribute to pioneering research in applying AI tools to assess and improve the quality of healthcare provided to children and adolescents who experience common behavioral and mental health challenges, including ADHD, autism, developmental delay, learning problems, anxiety and depression. Our team has been utilizing natural language processing of electronic health records (EHR) to gain insights from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen-AI), and retrieval-augmented generation (RAG). 

Tina Hernandez-Boussard, MS, MPH, PhD, is Professor of Medicine (Biomedical Informatics), of Biomedical Data Science, of Surgery and, by courtesy, of Epidemiology & Population Health, at Stanford. With a rich background and vast expertise in biomedical informatics, health services research, and epidemiology, she is at the forefront of advancing healthcare through the development, evaluation, and application of innovative methods. Through her research, she aims to effectively monitor, measure, and predict equitable healthcare outcomes. Her team is guided by Dr. Hernandez-Boussard’s mission to use AI to significantly enhance patient outcomes, streamline healthcare delivery, and provide valuable guidance for health policy decisions. Importantly, she also places significant emphasis on addressing bias and promoting fairness in AI for healthcare, aiming to both advance healthcare practices and ensure that diverse populations receive equitable resources, care, and outcomes, from this new technology.

Yair Bannett, MD, MS, is an Assistant Professor of Pediatrics (Developmental-Behavioral Pediatrics). Dr. Bannett’s research focuses on assessing and improving quality of care provided for children with attention-deficit/hyperactivity disorder (ADHD) and other behavioral and mental health conditions, while addressing disparities in care. Methods include artificial intelligence approaches for analyzing electronic health records data, quality improvement methodology, engagement of and collaboration with community stakeholders, and implementation science principles. The ultimate goal of Dr. Bannett’s research is to leverage technology to enhance equitable healthcare delivery and to improve health outcomes for children and adolescents with behavioral and mental health challenges.

We are seeking candidates interested in applying large language models to identify gaps in quality-of-care, detect adverse events in medication treatment of children, inform personalized treatment decisions in medication management, and implement evidence at the point of care to guide clinical decisions when treating children with behavioral and mental health challenges.

Goals of this postdoctoral position include: 1) leverage deep learning/large language models for extracting and analyzing information from clinical texts and 2) develop scalable solutions that can implemented in clinical settings to improve the quality of care for children and adolescents with mental health challenges. The scholar will create, test, deploy, evaluate, and publish these methods as an important addition to the Biomedical Informatics’ body-of-knowledge, with the purpose of improving clinical applications and enhancing medical care.

Required Qualifications: 
  • A PhD in one of the following: Biomedical Informatics, Computational Linguistics, Computer Science, Engineering, Health Services Research, or a related discipline
  • Excellent written and oral communication skills
  • Expertise and hands-on experience using LLMs, Machine Learning, Deep Learning frameworks, Natural Language Processing, etc.
  • Proficient programming skills in Python and R and working knowledge in SQL
  • Strong record of distinguished scholarly achievement
  • A strong publication record
  • Be willing, and able, to working in a collaborative research environment

 

Desired Skills and Experience:

  • A background in medicine/mental health or experience with research in healthcare domains is highly desirable
  • Database experience, preferably experience in SQL
  • Ability to work in a highly collaborative, results-driven, fast-paced environment
  • Ability to successfully interact with a diverse team, including clinicians, IT staff, and scientists across domains
  • Independent, and self-motivated researcher who is open to receiving feedback, as well as work with directed autonomy
  • Strong expertise in hands-on experience in using LLM for medical text processing
  • Ability to utilize LLMs, RL, and deep learning to build classification and predictive models for diverse applications in biomedical informatics (e.g., classifying patient outcomes in multiple domains, outcome prediction of treatment based on EHR)
  • Work with large-scale biomedical datasets (e.g., knowledge graphs) and patient electronic health records (EHRs)
  • Familiarity with biomedical terminology
  • Interest in equity, bias, and representation, in both evaluating the skews of datasets and the implementation of new technology tools for the benefit of patients
  • Interest and experience in mentoring and/or supervising younger scholars and their work
Required Application Materials: 
  1. Cover letter
  2. CV or résumé
  3. Career statement
  4. Example articles/manuscripts (top three strongest, preprints acceptable)
  5. Contact information for three references

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.