Careers

Job Description

CCB is looking for an individual to join the Data and Analytic Platforms Group, a group of engineers and scientists developing data warehousing and analytic solutions in support of epidemiology, healthcare economics, machine learning, and basic science research.

The Group works to reduce the burden on faculty by developing centrally managed and shareable data solutions to be used across research silos. We curate very large public and private healthcare utilization (insurance claims, electronic health record), multi-omics, environmental exposure, and social determinants data sets, provision access to those curated data sets, and develop analytic frameworks to accelerate reproducible academic research on top of them. Collectively these data sets contain information relating to hundreds of millions of patients.

This position reports to the Director of the CCB Data and Analytic Platforms Group. Primary responsibilities will include designing and implementing relational database architecture (schema, indexing, stored procedures, ETL processes, etc.) to warehouse multi-terabyte data sets in Microsoft SQL Server. This will include periodically evaluating various query performance metrics to ensure real-time availability to the research community and recommending modifications to the underlying database platform to resolve any identified issues. The bulk of this design work will be left up with the candidate, while a small portion will involve refactoring (or strategically deciding to abandon) existing ETL / indexing strategies. The data sets will be staged into a combination of proprietary schemas as well as the open-source i2b2 data model.

Additional opportunities will be available for the candidate to interact with individual scientific research teams to help improve their workflows.

Work Group

  • Data & Analytics Platforms

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

  • Genetics / Genomics

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 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.

Work Group

  • Genetics / Genomics

Requirements

  • 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 tojaclyn_mallard@hms.harvard.edu

Job Description

Research Scientist is a new academic, non-faculty track recently established at HMS. The candidate will be either Research Scientist or Senior Research Scientist, commensurate with experience and qualifications.

We are looking for a highly motivated collaborative individual who will help define strategic goals and will provide leadership in the adoption of tools and methods to analyze high-throughput omics data. The ideal candidate will have substantial experience in developing analytic methods for transcriptomics, epigenetics, metabolomics or other high throughput technologies such as CRISPR screens. They will have experience with machine learning approaches that can applied to integrate and learn from these data resources.

A strong background in developing and deploying software solutions for the methods they develop will be essential.

The successful candidate will help build a team that can support complex analyses of large data sets. They will help develop and deploy appropriate AI/ML approaches to analyze and interpret and integrate data sources to provide new insights.

Work Group

  • Genetics / Genomics

Job Duties

  • Providing scientific leadership and strategic planning
  • Managing people and projects
  • Implementing algorithms

Requirements

  • A PhD in Statistics, Computer Science or Computational Biology with expertise in machine learning or 10 years experience in the field
  • Strong communication skills
  • An ability to manage projects and teams in a dynamic academic environment
  • Expertise in designing and using algorithms to analyze single cell data such as RNA-seq, CITE-seq, spatial transcriptomics, metabolomics
  • Expertise in machine learning methods such as neural networks, Random Forests, Generative Adversarial Networks
  • Experience with TensorFlow or similar platforms
  • Experience with cloud deployment of software solutions
  • A track record of algorithm development accompanied to by robust software development (e.g., Bioconductor packages or Python modules)
  • Proven ability to integrate large complex data sources to extract knowledge

Send letter of interest and CV toJaclyn_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