- Develop and execute research projects focused on the integration of Large Language Models (LLMs), Natural Language Processing (NLP), and electronic health record (EHR) data in healthcare settings.
- Design and implement experimental methodologies for data collection, analysis, and interpretation.
- Algorithm Development and NLP Applications:
- Collaborate with interdisciplinary teams to design and develop NLP algorithms for extracting meaningful information from electronic health records.
- Apply LLMs to enhance NLP capabilities, improving the understanding and utilization of healthcare data.
- Preprocess and analyze large-scale electronic health record datasets, ensuring data quality, and extracting relevant clinical information.
- Apply statistical and machine learning methods to derive insights from healthcare data.
- Collaborate with clinical informaticians and healthcare professionals to understand the specific requirements and challenges in implementing LLMs and NLP in real-world healthcare environments.
- Integrate research findings into clinical informatics applications for improved healthcare decision-making.
- Conduct comprehensive literature reviews on relevant topics in LLMs, NLP, and electronic health record data in healthcare.
- Synthesize and critically analyze existing research to identify gaps and opportunities for contribution.
- Publication and Dissemination:
- Prepare research findings for publication in peer-reviewed journals and present at conferences, disseminating knowledge in the field.
- Collaborate with team members to contribute to conference abstracts and research posters.
- Assist in the development of grant proposals to secure funding for ongoing and future research projects.
- Provide expertise in LLMs, NLP, and electronic health record data to strengthen grant applications.
- Interdisciplinary Collaboration:
- Collaborate with researchers, healthcare professionals, and informaticians in interdisciplinary projects.
- Attend and actively contribute to research meetings, workshops, and seminars.
- Stay current with advancements in LLMs, NLP, and healthcare informatics technologies.
- Demonstrate proficiency in relevant programming languages (e.g., Python) and frameworks.
- Adhere to ethical standards in research, ensuring privacy and security of patient health data.
- Stay informed about ethical challenges and considerations in the intersection of healthcare, LLMs, and NLP.
- Maintain detailed documentation of research activities, methodologies, and results.
- Provide regular progress reports to project leaders, collaborators, and funding agencies.
- Teaching and Mentorship:
- Potentially contribute to teaching activities related to LLMs, NLP, and healthcare informatics.
- Provide mentorship and guidance to graduate and undergraduate students involved in related research projects.
- Actively engage in the academic and healthcare research community, building professional relationships.
- Attend conferences, seminars, and networking events to establish connections in the field of LLMs, NLP, and electronic health record data in healthcare.
- Proficiency with Python and MATLAB for signal processing and modeling.
- Biostatistical analysis skills, including bootstrapping, generating confidence intervals, and Bayesian statistics.
- Demonstrated ability in using software applications that either manage or analyze time series data and/or data from electronic health record.
- Experience with keeping a lab notebook in addition to code journaling and annotation.
- Proven ability to meet deadlines and work cooperatively in a small collaborative team.
- Demonstrated capability as a highly organized and creative problem-solver.
- Detail-oriented, self-motivated, and able to work independently as well as within cross-functional teams.
- Ability to adapt to rapidly changing and high-demand environments.
- Experience with the Spark big data stack (Hadoop, Spark, etc.) a plus.
- Comfort with probability, linear algebra, and data analysis, and experience processing or analyzing biological data.
- Excellent written and oral communication skills.
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Research Fellow - Boston, United States - Partners Healthcare System
Description
GENERAL SUMMARY/ OVERVIEW STATEMENT:
The Massachusetts General Hospital ICU Precision Medicine Lab, as part of the MGH Clinical Data Center and the National Patient-Centered CHoRUS for Equitable AI Collaboration, is seeking a Postdoctoral Fellow to participate in ongoing research studies focused on using NLP/LLM and machine learning and classification to develop methods for recognizing complex patient states for defining outcomes and performing risk prediction that have greater value compared to individual clinical parameters.
We are seeking a highly motivated Postdoctoral fellow who will have the opportunity to work with multi-year wide and deep data sets containing electronic health records, social determinants of health, and unstructured text data.
The incumbent should have a strong background in computer science, statistics, applied mathematics, or related fields with an outstanding track record.
In addition, the applicant should have excellent programming skills in MATLAB and Python and potentially have emerging experience with machine learning, neural networks, or deep learning frameworks.
The postdoctoral fellow will work with the PI and other members of the laboratory as well as collaborators to ensure smooth and successful outcomes for this research.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
The incumbent in this position will be responsible for:
Research Design and Implementation
SKILLS/ABILITIES/COMPETENCIES REQUIRED:
LICENSES, CERTIFICATIONS, and/or REGISTRATIONS:
Certification in Python preferred
EDUCATION:
PhD in engineering, physiology, neuroscience, data science, or related field
EXPERIENCE:
Experience with healthcare data preferred.
WORKING CONDITIONS:
The research fellow will work within a team of physicians, clinical research coordinators, and physician-scientist neurologists.
Work will be performed in the Center for NeuroTechnology and Neurorecovery Laboratory space, in collaboration and with other academic hospitals on the Massachusetts General Hospital main campus.
