Bioinformatics Analyst

Posted on by Charlie Johnson
Job ID:
Job date: 2014-09-29
End Date:

Company : Jackson Laboratory 

Country :

Role : Research Scientist 


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Job Description:

Job description

  The Jackson Laboratory for Genomic Medicine, based in Farmington, CT, is seeking a talented Bioinformatics Analyst to support Dr. Charles Lee’s Lab. This position offers the candidate excellent opportunity to gain experience in the field of genomic medicine and translational research. There will be several opportunities to make critical contributions to several projects under the supervision of scientists in the Lee lab. Position will be commensurate with qualifications, experience and aptitude.   Responsibilities:
  • Provide bioinformatics support for projects within the Lee Lab for both existing and future projects.
  • Participate in data processing, programming and algorithm development.
  • Design, develop and operate computational pipelines for analysis of high throughput multi-dimensional data.
  • Participate in evaluation of new technology platforms, assays and software.
 

Desired Skills and Experience

  • Ph.D. or MS with 2+ years’ experience in Bioinformatics, Biostatistics, Computational Biology or Computer Science. Exceptional candidates may be considered without experience.
  • Aptitude to work in a team environment is must.
  • Enthusiastic about learning new technologies, platforms and science.
  • Next generation sequence analysis (e.g. Whole Genome, Exome, RNASeq, ChipSeq).
  • Programming experience in Java, C/C++, Python, R, Perl.
  • Proficiency in UNIX scripting and various bioinformatics tools and databases.
  • Excellent communication skills.
  • Experience in microarray analysis (e.g. Expression, aCGH, SNP) is a plus.
  • Knowledge of basic statistical techniques and packages such as R/SAS/MATLAB.
  • Experience in analysis of large multi-dimensional genomic datasets.
  • Experience working in an HPC environment.
  • Experience in cancer biology preferred.
  • Experience in developing computational pipelines and algorithms for genomics research desired.

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