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.

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

Publications

Hopper RK, Abman SH, Elia EG, Avitabile CM, Yung D, Mullen MP, Austin ED, Bates A, Handler SS, Feinstein JA, Ivy DD, Kinsella JP, Mandl KD, Raj JU, Sleeper LA, . Pulmonary Hypertension in Children with Down Syndrome: Results from the Pediatric Pulmonary Hypertension Network Registry. The Journal of pediatrics 2022.

Wang X, Zhang HG, Xiong X, Hong C, Weber GM, Brat GA, Bonzel CL, Luo Y, Duan R, Palmer NP, Hutch MR, Gutiérrez-Sacristán A, Bellazzi R, Chiovato L, Cho K, Dagliati A, Estiri H, García-Barrio N, Griffier R, Hanauer DA, Ho YL, Holmes JH, Keller MS, Klann MEng JG, L'Yi S, Lozano-Zahonero S, Maidlow SE, Makoudjou A, Malovini A, Moal B, Moore JH, Morris M, Mowery DL, Murphy SN, Neuraz A, Yuan Ngiam K, Omenn GS, Patel LP, Pedrera-Jiménez M, Prunotto A, Jebathilagam Samayamuthu M, Sanz Vidorreta FJ, Schriver ER, Schubert P, Serrano-Balazote P, South AM, Tan ALM, Tan BWL, Tibollo V, Tippmann P, Visweswaran S, Xia Z, Yuan W, Zöller D, Kohane IS, Avillach P, Guo Z, Cai T, . SurvMaximin: Robust federated approach to transporting survival risk prediction models. Journal of biomedical informatics 2022.

Torous J, Stern AD, Bourgeois FT. Regulatory considerations to keep pace with innovation in digital health products. NPJ digital medicine 2022.

Levy S, Wisk LE, Minegishi M, Ertman B, Lunstead J, Brogna M, Weitzman ER. Association of Screening and Brief Intervention With Substance Use in Massachusetts Middle and High Schools. JAMA network open 2022.

Nielsen M, Presti M, Sztupinszki Z, Jensen AWP, Draghi A, Chamberlain CA, Schina A, Yde CW, Wojcik J, Szallasi Z, Crowther MD, Svane IM, Donia M. Co-existing alterations of MHC class I antigen presentation and IFNγ signaling mediate acquired resistance of melanoma to post-PD-1 immunotherapy. Cancer immunology research 2022.