Careers
Job Description
The Center for Computational Biomedicine (CCB) seeks an engaged computational scientist to join our team. The candidate will have strong statistical skills, good working knowledge of scientific programming and a strong interest in applying complex algorithms to epidemiological and omics data sets. The CCB has a number of active research projects in epidemiology and biomedical informatics as well as projects in spatial omics. Candidates should have skills in developing and implementing complex analysis methods to large data sets.
CCB is building an ecosystem of very large genomic and health services datasets, including a wide variety of covariate data sets including environmental exposures and social determinants. Combined, these data sets provide a powerful platform for studying health outcomes, epidemiology, health care policy and economics, health disparities, among many other research areas. These resources, along with the computational tools required to analyze them, will be available to enable the next generation of AI research applied to these areas. The Center has access to a cluster containing, in aggregate, over 11,000 compute cores, 90 TB of RAM, over 100 NVIDIA accelerator cards, and 10 PB of all-flash storage. In addition to the compute cluster, CCB maintains a number of large database servers each with 72 CPU cores, 3 TB of RAM, and 64 Gbps aggregate storage IO.
Work Group
- Computational Biology
Requirements
- Ph.D or equivalent in Statistics, Biostatistics, Computer Science or related field.
- Ability to develop complex and high performance algorithms and software infrastructures
- Experience and understanding of AI/ML algorithms and practices
- Good communication skills
- Ability to work on teams
Additional Qualifications
- Post-doc or work experience using advanced computational and analytic skills
- Understanding of high throughput biology (e.g. transcriptomics, imaging, flow cytometry, proteomics)
Send letter of interest and CV toJaclyn_Mallard@hms.harvard.edu
Job Description
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.
Work Group
- Computational Biology
Requirements
- 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.
Additional Qualifications
- 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
Job Description
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.
Job Duties
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.
Requirements
Skills
- 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
Qualifications
- An earned doctorate in a Biomedical Informatics-related field (epidemiology, statistics, computational biology, computer science, etc.)
Additional Qualifications
- 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
Job Description
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.
Work Group
- Data & Analytics Platforms