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 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.

Project Advocacy Interns will support the team in promoting projects, social media, compiling reports, working on event logistics, and pulling campaign metrics.


Diossy M, Sztupinszki Z, Borcsok J, Krzystanek M, Tisza V, Spisak S, Rusz O, Timar J, Csabai I, Fillinger J, Moldvay J, Pedersen AG, Szuts D, Szallasi Z. A subset of lung cancer cases shows robust signs of homologous recombination deficiency associated genomic mutational signatures. NPJ precision oncology 2021.

Abman SH, Mullen MP, Sleeper LA, Austin ED, Rosenzweig EB, Kinsella JP, Ivy D, Hopper RK, Usha Raj J, Fineman J, Keller RL, Bates A, Krishnan US, Avitabile CM, Davidson A, Natter MD, Mandl KD, . Characterisation of Pediatric Pulmonary Hypertensive Vascular Disease from the PPHNet Registry. The European respiratory journal 2021.

Lu FS, Nguyen AT, Link NB, Molina M, Davis JT, Chinazzi M, Xiong X, Vespignani A, Lipsitch M, Santillana M. Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches. PLoS computational biology 2021.

Aiken EL, Nguyen AT, Viboud C, Santillana M. Toward the use of neural networks for influenza prediction at multiple spatial resolutions. Science advances 2021.