Job Overview
The Machine Learning for Medical Language Lab at Boston Children's Hospital is seeking postdoctoral research fellows to work on natural language processing for biomedical text.
Fellows will develop new methods to extract information and make predictions from electronic health records and other biomedical writing.
Research areas of special interest include multimodal representation learning for clinical data, unsupervised domain adaptation of clinical machine-learning models, and graph-based neural representations of clinical text.
Applications span congenital heart disease, mental health, regulatory science, and infectious illness such as COVID-19, in collaboration with clinical researchers.
The fellow is expected to attend international conferences, publish papers, propose new projects, help prepare research proposals, and work with graduate and undergraduate students.
Mentorship is framed as preparation for a future leadership career in industry, academia, or government.
Qualifications are a PhD in computer science, math, physics, engineering, statistics, or a related technical field with interest in biomedical applications, plus research experience and strong written and oral communication.
Background in machine learning, NLP, medical terminologies, and libraries such as PyTorch, Transformers, TensorFlow, NumPy, and SciPy is encouraged.
The position is available immediately as a two-year fellowship.
Candidates apply by emailing a cover letter, CV, and sample publication to the email shown on the posting.
Original posting: https://labs.childrenshospital.org/tim-miller/jobs