Bioinformatics Analyst, Giannakis Lab

Job Details

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Job ID:
25045

Location:
450 Brookline Ave, Boston, MA 02215

Category:
IT/Informatics

Employment Type:
Full time

Work Location:
PTL Remote: 2-3 days remote/wk

Overview

Dr. Marios Giannakis at the Dana-Farber Cancer Institute (with co-affiliation at the Broad Institute of MIT and Harvard) is seeking a highly motivated, exceptional candidate to join his laboratory towards obtaining novel insights for the molecular epidemiology, treatment and associated response and resistance of colorectal cancer through the computational analysis of large-scale datasets including whole-exome, whole-transcriptome and single-cell RNA sequencing data. The successful candidate will lead and assist in projects integrating molecular, pathologic and clinical data as well as collaborate with a diverse array of community members both at the Dana-Farber Cancer Institute and the Broad Institute of MIT and Harvard. This individual will work towards analyzing some of the world’s most comprehensive and well-annotated biomedical datasets using novel and established computational approaches towards tackling several of the most pressing questions in cancer biology today. Consequently, there is unparalleled potential for your contributions to be published, used and recognized worldwide.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong.  As relentless as we are in our mission to reduce the burden of cancer for all, we are equally committed to diversifying our faculty and staff.  Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply. 

Requirements

  • Interprets complex biological information. Performs tasks to reduce and consolidate output from software. Prepares data for utilization by other scientists.
  • Monitors new data from public databases, finds and loads missed data, cleans loaded data to satisfy quality control criteria.
  • Must be able to query various sources for the information needed; i.e., the Web, publications and internal DFCI resources.
  • Directs and guides DNA, RNA and protein sequence database searches and the computational analysis of resulting data.
  • Implements end-users needs in database searching and integration.
  • Maintains the computational infrastructure and controls the flow of samples and information for large-scale studies. 
  • Recognizes and reports problems with the data management process and fixes the problems whenever possible
  • Leads and conducts computational biology and genomic research projects.
  • Analyzes large-scale biomedical data such as whole-exome and whole-genome sequencing, single-cell and bulk RNASeq data, functional genomic, microbiomic, metabolomic and other multi-dimensional datasets
  • Utilizes and develops computational tools for the analysis and integration of complex datasets
  • Conceives, implements and tests statistical models
  • Writes manuscripts, presents and publishes impactful research
  • Works together with experimental biologists to design experiments and analyze resulting data

Qualifications

  • BS, MS or PhD in Bioinformatics, Computer Science, Statistics, Life Sciences or any quantitative discipline  
  • Knowledge and experience with a wide range of biological databases and resources, such as TCGA, GenBank, EnsEMBL, the UCSC genome browser, and others
  • Strong statistical knowledge and programming using languages such as R, Python, Perl, MATLAB, Java R and related tools, as well as ability to prototype software solutions for data analysis
  • Background in computational biology, bioinformatics or other quantitative principle
  • Publication record is desired but not absolutely required
  • Excellent interpersonal and communication skills are essential.

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.

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