Job:Bioinformatics Postdoc in Aging, Harvard Medical School
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Job description

Computational Biology/Bioinformatics Post-doctoral position available immediately

To apply, send cover letter and CV to luis_rajman@hms.harvard.edu

We are seeking a talented, highly motivated individual to join the laboratory of Professor David Sinclair in the Genetics Department at Harvard Medical School, Boston. The Sinclair lab is known for their work on genes and small molecules that delay aging and treat age-related diseases. The lab has a wide range or expertise and interests, including cancer, neurodegeneration, diabetes, and fertility.

We are seeking a talented individual with a background in computational biology or bioinformatics. The position offers an opportunity to work with an engaged group of scientists and participate in cutting-edge research combining proteomics and genomics. The ideal candidate will have experience working with linux-based bioinformatic software and interactive data analysis environments (Python/R). The position requires expertise in genomics, transcriptomics, or proteomics data analysis. The candidate will work on integrative analysis of many types of omics data, including RNA-seq, ChIP-seq, Hi-C, and Quantitative Mass Spectrometry. The focus of the candidate will be on applying systems biology approaches to diverse data sets in order to address basic and translational research questions surrounding aging and age-associated diseases. This includes both the use of existing data analysis approaches and the development of new approaches and software. The individual will also participate in the development of our proteo-genomics data analysis efforts.

Principal Responsibilities:

  • Lead in the development of new methods,tools, algorithms, and pipelines to analyze and integrate genomic, epigenomic, transcriptomic, metabolomic, and proteomic data.
  • Work with the molecular biology team to design omics experiments.
  • Process, analyze and interpret high volumes of data as part of a wide range of internal and external scientific studies.
  • Provide bioinformatics support and consulting to other members of the laboratory.
  • Monitor and evaluate new and emerging technologies relevant to the lab (sequencing, proteomics and others).
  • Present scientific and technical data to both internal and external scientific colleagues in a clear and cohesive manner.
  • Work independently and prepare timetables, deliverables, and project schedules.

Required Skills/Abilities/Competencies:

  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, Biology, or related fields.
  • Extensive experience in scientific programming/scripting for analysis of biological data.
  • Proven understanding and experience in the fields of genomics, high-throughput sequencing, data processing, data analysis, and genomic databases.
  • Excellent track record of analyzing next generation sequencing data, particularly WGS, Hi-C, ChIP-seq, and RNA-seq.
  • Experience in linux-based environments.
  • Experience with statistical analysis is strongly preferred.
  • Strong scientific understanding of molecular and cellular biology, genetics and genomics.
  • Candidates must demonstrate outstanding personal initiative.
  • Excellent teamwork, time management and organizational skills.
  • Ability to work independently in a multidisciplinary, fast-paced, dynamic and results-oriented environment.
  • Ability to present data to a multidisciplinary audience in a clear and cohesive manner.
  • Ability to meet deadlines and multitask efficiently is a must.

The ideal candidate will have a record of scientific rigor and creativity, a strong publication record in peer-reviewed scientific journals and the ability to work in teams. Candidates should have a strong background in genomics, proteomics and metabolomics. Excellent oral and written communication skills are required. The individual will present regular updates to academic and industry collaborators as well as prepare and publish research reports. There is a real opportunity to invent and to innovate.

aging RNA-Seq Hi-C ChIP-Seq • 2.0k views
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