Harvard Medical School Instructor, Assistant, or Associate Professor
in the Computational Health Informatics Program
Boston Children’s Hospital
Boston, MA 

Establish your independent research program in computational health at Harvard and Boston Children’s Hospital.

CHIP, the Computational Health Informatics Program at Boston Children’s Hospital, an affiliate of Harvard Medical School and a collaborating program of its Department of Biomedical Informatics, is recruiting research faculty at junior and senior levels to join us in transforming care delivery and biomedical science.

We seek outstanding candidates passionate about advancing the ability to acquire and then reason over an entire spectrum of data types ranging from clinical, epidemiological, environmental and social, all the way down to molecular and genomic.  

Candidates expert in health IT architectures and standards (e.g. SMART on FHIR apps and infrastructure) will be given special consideration. Areas of focus can include machine learning/AI including clinical decision support and predictive medicine, precision medicine, population health, real-world evidence and data visualization. 

Candidates at the Instructor or Assistant Professor level should have strong quantitative backgrounds and a history of innovative approaches to biomedical scientific inquiry or the translation of computational methods to engineering or software applications in medicine. Candidates at the Associate Professor level must additionally demonstrate scientific leadership and the ability to develop sustainable, impactful projects.

All qualified applicants must have a doctoral degree (MD, PhD, MD/PhD, or equivalent) and a strong record of publishing. Faculty are expected to teach, be exceptional mentors and have or achieve substantial independent funding.

CHIP, founded in 1994, 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. Though CHIP has a robust pediatric research agenda, our interests span across all ages. CHIP research highlights are here.

For the work of CHIP, Health 2.0 voted Boston Children’s Hospital the 10 Year Global Retrospective Top Influencer among all health care organizations.

Boston Children’s Hospital is an equal opportunity employer that strongly encourages women and underrepresented minorities candidates apply for positions at our institution.

Interested applicants should submit a CV, cover letter, research plan, three references and three letters of support to Kenneth D. Mandl, MD, MPH, CHIP Director by emailing them to Megan Rollins (megan.rollins@childrens.harvard.edu) by February 1, 2021.

Applications may be considered on a rolling basis so there could be an advantage to submitting early.

 

Publications

Zhang A, Teng L, Alterovitz G. An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis. Journal of the American Medical Informatics Association : JAMIA 2020.

Geva A, Stedman JP, Manzi SF, Lin C, Savova GK, Avillach P, Mandl KD. Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data. JAMIA open 2020.

Börcsök J, Sztupinszki Z, Bekele R, Gao SP, Diossy M, Samant AS, Dillon KM, Tisza V, Spisák S, Rusz O, Csabai I, Pappot H, Frazier ZJ, Konieczkowski DJ, Liu D, Vasani N, Rodrigues JA, Solit DB, Hoffman-Censits JH, Plimack ER, Rosenberg JE, Lazaro JB, Taplin ME, Iyer G, Brunak S, Lozsa R, Van Allen EM, Szüts D, Mouw KW, Szallasi Z. Identification of a synthetic lethal relationship between nucleotide excision repair (NER) deficiency and irofulven sensitivity in urothelial cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2020.

Gokuldass A, Draghi A, Papp K, Borch TH, Nielsen M, Westergaard MCW, Andersen R, Schina A, Bol KF, Chamberlain CA, Presti M, Met Ö, Harbst K, Lauss M, Soraggi S, Csabai I, Szállási Z, Jönsson G, Svane IM, Donia M. Qualitative Analysis of Tumor-Infiltrating Lymphocytes across Human Tumor Types Reveals a Higher Proportion of Bystander CD8 T Cells in Non-Melanoma Cancers Compared to Melanoma. Cancers 2020.

Perera G, Rijnbeek PR, Alexander M, Ansell D, Avillach P, Duarte-Salles T, Gordon MF, Lapi F, Mayer MA, Pasqua A, Pedersen L, van Der Lei J, Visser PJ, Stewart R. Vascular and metabolic risk factor differences prior to dementia diagnosis: a multidatabase case-control study using European electronic health records. BMJ open 2020.