Postdoctoral Scholar

The Boussard Lab in the Division of Biomedical Informatics (BMIR), in the Department of Medicine at Stanford University is seeking highly motivated, passionate postdoctoral scholars looking to make an impact in the field of health-related informatics.

Candidates are welcome from a variety of inter-related backgrounds such as biomedical informatics, computer science, electrical engineering, 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.

A postdoc position in the Boussard Lab offers motivated candidates an opportunity to contribute to pioneering research in areas such as: Large Language Models (LLM) processing of electronic health records (EHR); using AI to gain clinical-analytical insights from real world data; Reinforcement Learning and Deep Learning predictive models; leveraging Natural Language Processing (NLP) for medical insight; and much more.

The lab is led by Tina Hernandez-Boussard, MS, MPH, PhD, 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.

The lab’s scope of research spans a spectrum of biomedical domains involving many multidisciplinary collaborations with top scientists at both at Stanford and at other institutions internationally.

Postdoctoral fellows will be involved in the analysis of large heterogeneous datasets, including electronic health records, unstructured clinical notes, administrative data, registry data, and patient surveys to inform clinical decisions and guide policy. We are seeking candidates interested in multi-modal and multi-task learning, weak supervision, knowledge representation, NLP, and decision theory to identify the right treatment for the right patient, patients at high risk for adverse events, and to implement evidence at the point of care to guide clinical decisions.

Goals of at Boussard Lab postdoc include: 1) develop foundational AI methods for analyzing and extracting information from clinical texts; and 2) develop clinical prediction models using multi-modal and longitudinal EHR data. 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 transform medical care for the better.

Requirements

  • 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, NLP, etc.
  • Proficient programming skills in Python and R or another relevant programming language commonly used in data science and natural language processing
  • 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

  • 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
  • A background in medicine or other related healthcare field is highly desirable
  • Strong expertise in hands-on experience in using LLM for medical text processing
  • Ability to utilize LLMs, RL, and deep learning to build predictive models for diverse applications in biomedical informatics (e.g., computational drug repurposing, and 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

Terms

A postdoc term is usually 2 years, though this may vary. Position availability is hinged on funding; and applications are reviewed on a rolling basis. If this information page is active, then one or more positions are being recruited for so please apply.

To Apply

To begin the application process, please send the following to Tina Hernandez-Boussard, PhD at boussard AT stanford DOT edu.

  1. Cover letter
  2. CV or résumé
  3. Career statement
  4. Example articles/manuscripts (top three strongest)
  5. Contact information for three references

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