Mount Sinai Careers
BIOINFORMATICIAN I - GENETICS/GENOMIC SCIENCES
Strength Through Diversity
Ground breaking science. Advancing medicine. Healing made personal.
The Bioinformatician I will work with a group of researchers/biologists on innovative genomic analyses of structural variation, epigenetics, and gene expression in an integrated environment combining experimental and bioinformatic approaches to human disease. The individual will support research projects by delivering bioinformatics services for bio-medical data from cutting-edge genomic technologies
The ideal candidate will have strong statistical and programming proficiencies with proven expertise in genomic analysis.
- Writes custom scripts for analysis of genomic data derived from high-throughput techniques.
- Designs and implements bioinformatics tools and processes in order to analyze large scale datasets.
- Identifies and resolves technical issues and proposes upgrades to current software.
- Develop projects and work independently on a variety of bioinformatics analysis projects.
- Manages databases, conducts statistical and genomic analysis, and participates in the preparation of manuscripts and presentations.
- May be involved in sequence and structural analysis, data mining, or statistical modeling.
- May collaborate with wet-bench biologists and work independently to analyze data derived from several types of projects using microarrays and high-throughput sequencing.
- May conduct analysis of microarray and high-throughput sequencing data, genome sequence analysis, experimental design and statistical analysis.
- May give presentations both inside and outside of the institution.
- Other related duties as assigned.
- B.S. in Biological Sciences, Bioinformatics, Computer Sciences, Statistics or related discipline; M.S. preferred
- Good organization and communication skills, with demonstrated ability to productively work as a member of a team. Strong verbal and written communication skills in English are required
- 3 years experience required
- Working experience with genetics or statistics analysis software and online resources. Experience in programming environments such as Matlab, R statistical package, BioConductor, Perl or C++.