Postdoctoral Training

There is a common core of knowledge, skills, and experiences to engage meaningfully in the field of informatics. CHIP offers training at many levels and is well integrated with the vibrant academic community at the Harvard Department for Biomedical Informatics and affiliated hospital-based training programs, providing fellows with many opportunities for interaction and collaboration.

The Computational Health Informatics Program (CHIP) at Boston Children’s Hospital hosts a training program for postdoctoral fellows to be trained in Informatics, Genomics, Machine Learning, Artificial Intelligence, and Biomedical Data Science.

The Health Natural Language Processing Lab at Boston Children’s Hospital is seeking a post-doctoral research fellow to contribute to cutting edge research in the field of health natural language processing.

The Clarity- and Virtue-guided Algorithms (CAVA) Lab at Boston Children's Hospital / Harvard Medical School is seeking a post-doctoral research fellow to advance the interpretability and fairness of machine learning (ML) models deployed in critical healthcare settings.

The Lee Lab in the Vascular Biology Program at Boston Children’s Hospital invites applications for a postdoctoral fellow position in the field of artificial intelligence-based analysis of biomedical spatiotemporal data.

Internships

The Boston Children's Hospital Computational Health Informatics Program (CHIP) is Harvard Medical School affiliated, multidisciplinary applied research and education program. CHIP is uniquely positioned at the nexus of a world-leading children’s hospital, a first-rate academic institution, wider health networks, and thoughtful collaborations with industry.

Our research has been at the forefront of posing a wide spectrum of health questions and building solutions. Our faculty advance the science of biomedical informatics for molecular characterization of the patient, gene discovery, medical decision making, diagnosis, therapeutic selection, care redesign, public health management, population health, and re-imagined clinical trials. Our research has influenced public health policies at the highest level. Governmental health institutions, like the Centers for Disease Control and Prevention, have amended their recommendations for population health based on the research of our faculty. Our faculty have advised governments worldwide on establishing biodefense and biosurveillance infrastructures. The White House, US State Department, USAID, and NASA have recognized our faculty for their research contributions in health care.

CHIP has a longstanding track record of developing and repurposing existing technologies that have been widely commercialized. We have established partnerships with  companies like Uber, Lyft, Quest Diagnostics, and Eli Lily and have developed platforms that have been widely adopted by Apple, Google, Microsoft, and Amazon.

The CHIP AI Internship is an opportunity for undergraduate students at Harvard College to develop new machine learning and artificial intelligence approaches and apply them to fundamental challenges in biomedicine.

Publications

Keloth VK, Banda JM, Gurley M, Heider PM, Kennedy G, Liu H, Liu F, Miller T, Natarajan K, V Patterson O, Peng Y, Raja K, Reeves RM, Rouhizadeh M, Shi J, Wang X, Wang Y, Wei WQ, Williams AE, Zhang R, Belenkaya R, Reich C, Blacketer C, Ryan P, Hripcsak G, Elhadad N, Xu H. Representing and Utilizing Clinical Textual Data for Real World Studies: An OHDSI Approach. Journal of biomedical informatics 2023.

Toce MS, Michelson KA, Hudgins JD, Olson KL, Monuteaux MC, Bourgeois FT. Association of prescription drug monitoring programs with benzodiazepine prescription dispensation and overdose in adolescents and young adults. Clinical toxicology (Philadelphia, Pa.) 2023.

Brown T, de Salazar Munoz PM, Bhatia A, Bunda B, Williams EK, Bor D, Miller JS, Mohareb A, Thierauf J, Yang W, Villalba J, Naranbai V, Garcia Beltran W, Miller TE, Kress D, Stelljes K, Johnson K, Larremore D, Lennerz J, Iafrate AJ, Balsari S, Buckee C, Grad Y. Geographically skewed recruitment and COVID-19 seroprevalence estimates: a cross-sectional serosurveillance study and mathematical modelling analysis. BMJ open 2023.

El-Hayek C, Barzegar S, Faux N, Doyle K, Pillai P, Mutch SJ, Vaisey A, Ward R, Sanci L, Dunn AG, Hellard ME, Hocking JS, Verspoor K, Boyle DI. An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice. International journal of medical informatics 2023.

Patik I, Redhu NS, Eran A, Bao B, Nandy A, Tang Y, El Sayed S, Shen Z, Glickman J, Fox JG, Snapper SB, Horwitz BH. The IL-10 receptor inhibits cell extrinsic signals necessary for STAT1-dependent macrophage accumulation during colitis. Mucosal immunology 2023.