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Bioinformatician

Employer
Howard Hughes Medical Institute
Location
Worcester, Massachusetts

About HHMI
Howard Hughes Medical Institute (HHMI) is a science philanthropy whose mission is to advance biomedical research and science education for the benefit of humanity. We empower exceptional scientists and students to pursue fundamental questions about living systems, and work to share scientific discoveries with researchers, students, and science-curious individuals around the world. Founded in 1953 by aviator and industrialist Howard R. Hughes, HHMI is headquartered in Chevy Chase, Maryland, and employs more than 2,500 people across the U.S. Visit hhmi.org/careers to learn more about working at HHMI.

Opportunity

We are seeking a highly motivated bioinformatician to join Dr. Job Dekker’s group in the Program in Systems Biology at the University of Massachusetts Medical School. This position will involve working with a multi-disciplinary team of molecular biologists, statisticians and bioinformaticians as we develop and leverage technological breakthroughs to explore the biology of complex systems. The bioinformatician will be responsible for the design, development, testing, evaluation and maintenance of bioinformatics tools. These tools are used to process, analyze and organize deep-sequencing data to study three-dimensional genome organization. Visit our lab website to learn more about our work:
http://jobdekkerlab.umassmed.edu/

Principal Responsibilities

  • Design and implement reusable bioinformatics analysis pipelines for processing next-generation sequencing, microarray, genomics, proteomics and chemogenomics data
  • Integrate computational methods/pipelines with high performance computing clusters
  • Collaborate closely with Investigator and lab members on research projects including defining the scope of the collaboration, researching the scientific topics and implementing the appropriate bioinformatics solutions that meet project timelines
  • Participate in the oral presentation of all project findings and abstracts including participation in periodic project status meetings and presentation of final project deliverables
  • Develop rapid prototypes and custom scripts for one-off type of analysis requests
  • Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate
  • Properly document the procedures used in computational analysis and provide summary report of results suitable for inclusion in manuscripts and grant applications
  • Establish and customize genomic, proteomics databases and provide batch analysis utilities that make use of these resources
  • Develop custom databases and web portals for managing raw and processed experimental data
  • Provide bioinformatics training and workshops for analysis pipelines and in-house developed software applications
  • Coordinate and collaborate with other bioinformaticians, biostatisticians, information technology professionals, and interdepartmental project teams
  • Perform other duties as required

Preferred Qualifications

  • Master's degree in Computer Science or Bioinformatics or a related computational discipline, or equivalent experience
  • Strong background in programming and algorithms. Fluent in one programming language (Python, C, C++ or Java) and familiarity with scripting languages (bash, Perl)
  • Knowledge of Unix operating system, terminal and bash
  • Excellent oral and written communication skills as well as the ability to collaborate effectively with a diverse team
  • Familiarity with programming techniques for analyzing data sets that do not fit in memory
  • Numpy/Scipy/HDF5 experience is a plus
  • Experience working with BIG DATA (NGS data in multi-TB scale)
  • Experience using relational databases, SQL and / or structured data formats (e.g. HDF5)
  • Web programming experience (PHP, Django, JavaScript, JQuery, JSON, REST API) is a plus
  • Experience using genome alignment software (bowtie2, bwa, tophat, etc.) is a plus
  • Experience using a compute cluster (LSF, SGE)
  • Co-authorships on peer-reviewed publications are preferred

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