Harvard T.H. Chan School of Public Health
Degree Level Required:
We are seeking a talented and highly motivated Bioinformatician to join our dynamic, collaborative team focused on high-throughput sequencing (HTS) applications. The ideal candidate will have experience analyzing and interpreting Omics data, and is enthusiastic to share their expertise through the core’s consulting and education programs.
In this role, you will:
- Support selected research projects, working independently with researchers at the Harvard Chan School, Harvard and the broader Boston biomedical community.
- Provide expertise in the use of specialized bioinformatic tools and analysis methods to researchers and collaborate in analyzing and interpreting their data.
- Teach workshops and develop new training content geared towards graduate students, postdocs, research staff and faculty.
- Coordinating closely with other Core staff, the candidate will analyze incoming data using existing analytical approaches commonly used in the Core, and assess and/or develop new methods where appropriate.
- Documenting work thoroughly, and provide manuscript-level reporting of final analyses and results.
- Summarize, analyze and visualize data using advanced techniques, and provide direct links to related informatics analysis tools.
- Other duties will include data management (coordinating with collaborating Research Computing groups and Core developers to ensure consistent data storage), liaising with collaborating researchers and participating in teaching/developing workshops.
- Doctoral degree in biological sciences, statistics or related computational field (eg. Bioinformatics, Computational Biology, Genomics, Biostatistics or Biological Sciences) required, with working knowledge of molecular biology
- At least 2 years of postdoctoral experience in academia or industry using a broad range of current bioinformatics approaches for common applications.
- Expertise in at least one of the following HTS applications is required: Whole genome or exome-sequencing, Transcriptomics (bulk, small or single cell RNA-seq), Epigenomics (ChIP-seq or ATAC-seq)
- Demonstrable ability to apply statistical approaches to analyze data, interpret and present results
- A strong interest in teaching
- Excellent analytical and programming skills
- Excellent communication and time management skills