The Center for Computational Biomedicine (CCB) at Harvard Medical School (HMS) is looking for an experienced Computational Biologist to advance in CCB’s mission to leverage data and computation to transform research and improve health. CCB provides computational and analytic resources to advance scientific discovery within HMS through its multi-disciplinary team of computational and quantitative scientists who work on collaborative projects both within the center and with members of the HMS community.
The role will involve processing, analyzing, and integrating public and newly generated single-cell and spatial multi-omics datasets in collaboration with experimental labs at HMS. This will include developing sustainable tools, software packages, and integrated data science products that empower research labs to explore, analyze, and interpret their data. The data sources will often be at the leading edge of scientific discovery and will therefore require methodological work, algorithm development, and technical developments.
The ideal candidate will be proficient in R and/or Python, have strong quantitative, analytical, and communication skills, and will be able to work independently and collaboratively on scientific problems and deliver solutions. There will be opportunities for working in teams and independent decision making at all levels of bioinformatic processing and statistical analysis of the data, as well as examining, evaluating, and recommending analytical approaches to collaborating labs. In addition, methodological developments for novel and challenging data analysis and integration tasks arise frequently requiring originality and creativity, including designing and analyzing follow-up experiments.
- Computational Biology
- PhD in Bioinformatics, Computational Biology, Biostatistics, Computer Science, Statistics or related fields,
- Substantial experience analyzing genetic, genomic, or image data,
- Ability to program at a high level in R or Python,
- Ability to work independently.
- Experience with analyzing single-cell and spatial omics data,
- Working knowledge of git or similar tools for scientific software development,
- Experience writing data publishing tools that support user interaction such as RStudio’s Shiny or Connect applications,
- Experience with machine learning frameworks such as TensorFlow or PyTorch,
- Ability to work on teams,
- Strong communication skills.
Interested applicants should send their CV and cover letter to Jaclyn Mallard.Jaclyn_Mallard@hms.harvard.edu
The Center for Computational Biomedicine (CCB) at Harvard Medical School is looking for an experienced Statistical Geneticist to take a leading role in its mission to support the broad use of leading edge computational and analytic methods at HMS. The CCB is a new center whose mission is to provide computational expertise in a variety of areas including: genetics, genomics, AI/ML and image analysis. The candidate will be either Data Scientist or Senior Data Scientist, commensurate with experience and qualifications.
The role involves working with various labs in HMS providing expertise in analyzing, visualizing and integrating genetic and genomic data. The data sources will often be at the leading edge of scientific discovery and technical development and some methodological work may be required. The successful candidate will have strong skills in R or Python, strong quantitative and communication skills. They will be able to work independently and collaboratively on scientific problems and deliver solutions.
The CCB is a new center in HMS that will provide computational and analytic resources to advance scientific discovery within HMS. It has a multi-disciplinary team of computational and quantitative scientists who work collaboratively both within the center and with members of the HMS community.
- Computational Biology
- PhD in Human Genetics or a related field with substantial experience working with genetic data
- Strong quantitative skills
- Technical expertise in software development
- Ability to program at a high level in R or Python
- Substantial experience analyzing genetic or genomic data at scale
- Ability to work independently
- Working knowledge of git or similar tools for software development
- Experience building imputation panels, LD servers, analyzing genetic data from diverse populations, GWAS at scale
- Ability to work on teams and to lead teams or projects
- Strong communication skills
Send letter of interest and CV email@example.com
The Center for Computational Biomedicine (CCB) at Harvard Medical School is seeking a Postdoctoral Fellow with experience in biomedical data science or a related field, such as population genetics, biostatistics, or epidemiology. You will work with Robert Gentleman, Executive Director of the Center, to analyze large datasets, merging epidemiological, environmental exposure, social determinants, and genetic data. The goal of our efforts is to usher in a new age of precision medicine through combining demographic, environmental, and epidemiological data to enable the study of disease trajectories, comorbidities, and environmental effects that modify risk.
We will use AI/ML methods, multiple imputation, and data integration on complex (e.g. NHANES) and very large health insurance data sets. Approaches will include Environment-wide Association Studies (EnWAS), statistical modeling, and visualization.
- Proficiency with big data analytics including scripting languages such as R and python;
- Proficiency in the use of SQL databases;
- Familiarity with HPC clusters and distributed computing architectures
- An earned doctorate in a Biomedical Informatics-related field (epidemiology, statistics, computational biology, computer science, etc.)
- Self-motivated and highly detail oriented
- Strong technical/systems design and development skills
- Strong problem solving, testing, and debugging skills
- Solid understanding of research data systems and database design
- Excellent verbal and written communication skills
- A solution-focused attitude and ability to apply their skills to multiple projects at a time
- Interest in warehousing of large patient and cohort databases
To be considered for this position, please email a single PDF document containing a letter of application that addresses your interest in and qualifications for the position, and a curriculum vitae. Please include the names and contact information of three references, who will be asked to supply letters or will be contacted by phone early in the application process. This is a one-year term appointment with options for renewal. The position is available now at Harvard Medical School in Boston. Address applications to: Robert Gentleman Executive Director CCBJaclyn_Mallard@hms.harvard.edu
We seek a highly motivated, collaborative individual with excellent communication skills to join our team of technologists and scientists as a Senior Software/Data Engineer. You will help to design and implement novel solutions to standardize (meta)data using ontologies, with the goal of integrating large, complex, heterogeneous datasets. The datasets include healthcare insurance claims, electronic health records, genomics, environmental exposure, among others. The integration of these data will support large-scale epidemiological research in precision medicine, healthcare, and basic science, all with the goal of improving patient outcomes.
In this role, you will leverage ontologies and automated reasoning to develop sophisticated data and knowledge discovery solutions. Your work will use a wide variety of technologies, including ontology APIs and tools (e.g., OWL API, owlready2), public and protected relational and graph databases, and containerized services. You will have strong skills in Python or Java, and research experience or experience working in a research environment. You will be able to work independently and collaboratively on scientific and engineering problems and deliver solutions.
- Data & Analytics Platforms