Postdoctoral Positions in the Lab of Paul Avillach

Areas of focus

Phenotype extraction and biomedical ontologies

The Department of Biomedical Informatics (DBMI) at Harvard Medical School is looking for a Postdoctoral Fellow to help build cutting edge research platforms. The real value in biomedical research lies not in the scale of any single source of data, but in the ability to integrate and interrogate multiple, complementary datasets simultaneously. We are combining clinical and genomics data across different scales and resolutions to enable new perspectives for essential biomedical questions. The research focuses on the development of novel methods and techniques for the integration of multiple heterogeneous clinic cohorts, Electronic Health Records data and multiple types of genomics data to encompass biological observations.


The Postdoctoral Fellow will be responsible for developing novel methodologies and applications to facilitate high-throughput phenotype extraction, harmonize content with biomedical ontologies and integrate clinical and molecular genomic data.

The diversity of subject matter will require a creative mind and a candidate capable of deploying imaginative strategies and who is dedicated to solving complex and challenging problems within an interdisciplinary environment.

Basic Requirements

Candidates must have a PhD degree (or MD/PhD.) in biomedical informatics, bioinformatics, Computational Biology, computer science, or a related field. Curriculum in and/or experience with standardized ontologies, terminologies, metadata, and related technologies as well as experience in programming and software development will be necessary for this opportunity. The candidate interested in this position must be highly motivated, willing to learn and demonstrate initiative in assigned tasks. Excellent written and verbal communication skills are crucial.

Additional Requirements

Preferred requirements for this position include experience with the Unified Medical Language System (UMLS), statistics, data mining and machine learning. Experience with R, Python, and/or Perl is desirable.


The position is available immediately and can be renewed annually.

How to apply

Email applications including curriculum vitae, summary statement of personal objective and research interests, PDFs of the best two papers, and the names and email addresses of three references to

Harvard Medical School is an Equal Opportunity/Affirmative Action Employer.

Women and minorities are especially encouraged to apply.

For additional information contact

Paul Avillach, MD, PhD
Assistant Professor
Department of Biomedical Informatics | Harvard Medical School
Children’s Hospital Informatics Program | Boston Children's Hospital 

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Drug-drug interaction detection in real-world claims data and healthcare records (Harvard-MIT Center for Regulatory Science)

The Harvard Program in Therapeutic Science (HiTS) invites applications for a fellowship position at the Harvard-MIT Center for Regulatory Science. The fellow will work with a multidisciplinary team to develop and evaluate novel computational methods to support automated detection of drug-drug interactions in large and disparate healthcare datasets. 

About the Fellowship

The Harvard-MIT Center for Regulatory Science is a partnership between Harvard, MIT and the FDA, focused on building innovative approaches for the development and evaluation of medical products. Working across academia, industry, and government institutions, the Center promotes regulatory science through research and education programs, uniting stakeholders under a common mission: promoting optimal patient health outcomes through biomedical innovation and the availability of safe and effective diagnostics and treatments. The Regulatory Science Fellows Program draws individuals of diverse experiences who are passionate about using novel applications of data science to improve the use of therapeutics in patient populations.

For this position, the Fellow will work with faculty at Harvard in the Department of Biomedical Informatics The fellow will be based in the Avillach Lab, an interdisciplinary research group focused on the development of cutting edge techniques for the integration of multiple heterogeneous biological and clinical cohorts with the overarching goal of supporting individualized data-driven healthcare.

Project Details

The application of healthcare claims data and electronic health records for use in pharmacoepidemiological studies is booming. Drug–drug interactions can be identified by mining such databases, including adverse drug reactions (ADRs) resulting from the prescription of a combination of drugs (CADRs), considered a special class of drug-drug interactions. While many ADRs can be anticipated and hence avoided, CADRs are highly complex and challenging to identify and, as a consequence, have not been well studied. CADRs may represent as many as 30 % of unexpected ADRs and their elucidation is of particular interest to the FDA. The fellowship project will develop new signal detection algorithms using data mining techniques in real-world healthcare data derived from claims and electronic healthcare records. The project will aim to identify potential pharmacovigilance signals concerning drug-drug interactions across multiple diseases and syndromes.

Research activities include, but are not limited to:

  • Extract and analyze information from a nationwide claims database including 67 million subjects
  • Extract and analyze information from healthcare records in an academic pediatric hospital including 1.8 million patients
  • Develop and test methods to detect adverse drug reactions from billing codes, drug prescriptions and lab value results
  • Disseminate findings through national and international conferences and in peer-reviewed scientific publications
Basic Qualifications
  • PhD in computer science, engineering or a related field
  • Expertise in SQL query language
  • Expertise in R or Python programing languages
Application Procedure and Requirements 

Applications will be accepted until the position is filled. Please include the following when applying:

  • Curriculum vitae
  • Cover letter and a 2-page description of relevant experience as a single PDF
  • DOI or PMCID of up to three relevant publications

Selected candidates will be asked to provide letters of reference.

Position Description

Host Institution: Harvard Medical School
Appointing Department: Harvard Program in Therapeutic Science
Research Laboratory: Paul Avillach
Location: Boston, MA
Category: Scientist
Other responsibilities: no administrative or teaching obligations
Duration of fellowship: 2 years

Harvard Medical School is an Equal Opportunity/Affirmative Action Employer.

Women and minorities are especially encouraged to apply.

For additional information contact

Paul Avillach, MD, PhD
Assistant Professor
Department of Biomedical Informatics | Harvard Medical School
Children’s Hospital Informatics Program | Boston Children's Hospital

Paul Avillach

Paul Avillach, MD, PhD

Associate Professor of Biomedical Informatics, Harvard Medical School
Assistant Professor of Pediatrics, Boston Children's Hospital
Assistant Professor in the Department of Epidemiology, Harvard T.H. Chan School of Public Health

Avillach Lab