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 program is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) at the National Institutes of Health (T32HD040128-16) and is open to US citizens and permanent residents.

CHIP, an affiliate of Harvard Medical School and a collaborating program of the Harvard Medical School Department of Biomedical Informatics, is recruiting postdoctoral fellows. Founded in 1994, CHIP is a multidisciplinary applied research and education program. Biomedical informatics has become a major theme and methodology for biomedical science, health care delivery, and population health, involving high-dimensional modeling and understanding of patients from the molecular to the population levels. We design information infrastructure for medical decision making, diagnosis, care redesign, public health management, and re-imagined clinical trials. The field is inherently interdisciplinary, drawing on traditional biomedical disciplines, the science and technology of computing, data science, biostatistics, epidemiology, decision theory, omics, implementation science, and health care policy and management. Our faculty are trained in medicine, data science, computer science, mathematics and epidemiology. Our faculty have been featured in The New York Times, Wall Street Journal, ABC News, CNBC, Bloomberg, CNN, Forbes, Financial Times, NBC News, GQ Magazine, U.S. News & World Report, Politico, and BBC News for their expertise on COVID-19.

We seek outstanding candidates passionate about advancing the ability to acquire and then reason over an entire spectrum of data types ranging from molecular and genomic all the way to clinical, epidemiological, environmental and social. Focus areas may include, but are not limited to research applications of machine learning/AI including COVID-19, medical applications of machine learning/AI including clinical decision support and predictive medicine, genomic and precision medicine, population health, health IT architectures and standards (e.g. SMART on FHIR apps and infrastructure), re-imagined clinical trials, real-world evidence, data visualization, and integrative omics. Candidates should have strong quantitative backgrounds.

Over the past two decades, the program has trained a mix of MDs and PhDs. More than 90 percent have gone on to receive independent funding in faculty positions in academic medicine.

Click here to learn more.

Admissions

Applications are open, and admissions are available on a rolling basis.

Eligibility

Citizens or permanent residents of the United States enrolled in a research doctoral, research postdoctoral, clinical doctoral, or clinical postdoctoral are eligible to apply. Preference will be given to candidates who have, or are seeking, board certification in pediatric emergency medicine, or who have research interests that are aligned with CHIP’s core research areas.

The program has been committed to recruiting and retaining postdoctoral trainees who are URiM. We have maintained our commitment to diversity through prioritizing applications from diverse and disadvantaged backgrounds. Women and underrepresented minority groups are strongly encouraged to apply.

How to apply

Click here to ask questions.

To apply, send a CV, cover letter, personal statement, and three letters of reference to megan.rollins@childrens.harvard.edu.

Publications

Geisler BP, Zahabi L, Lang AE, Eastwood N, Tennant E, Lukic L, Sharon E, Chuang HH, Kang CB, Clayton-Johnson K, Aljaberi A, Yu H, Bui C, Le Mau T, Li WC, Teodorescu D, Hinske LC, Sun DL, Manian FA, Dunn AG. Repurposing existing medications for coronavirus disease 2019: protocol for a rapid and living systematic review. Systematic reviews 2021.

Börcsök J, Diossy M, Sztupinski Z, Prosz A, Tisza V, Spisak S, Rusz O, Stormoen DR, Pappot H, Csabai I, Brunak S, Mouw KW, Szallasi Z. Detection of Molecular Signatures of Homologous Recombination Deficiency in Bladder Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2021.

Geva A, Albert BD, Hamilton S, Manning MJ, Barrett MK, Mirchandani D, Harty M, Morgan EC, Kleinman ME, Mehta NM. eSIMPLER: A Dynamic, Electronic Health Record-Integrated Checklist for Clinical Decision Support During PICU Daily Rounds. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies 2021.

Li J, Tiwari A, Mirzakhani H, Wang AL, Kho AT, McGeachie MJ, Litonjua AA, Weiss ST, Tantisira KG. Circulating MicroRNA: Incident Asthma Prediction and Vitamin D Effect Modification. Journal of personalized medicine 2021.

Larsen RJ, Gagoski B, Morton SU, Ou Y, Vyas R, Litt J, Grant PE, Sutton BP. Quantification of magnetic resonance spectroscopy data using a combined reference: Application in typically developing infants. NMR in biomedicine 2021.