Scientist I - Single cell transcriptomic approaches

Less than 5 years experience  • 

Salary depends on experience
Posted on 03/21/18
Less than 5 years experience
Salary depends on experience
Posted on 03/21/18

Job Responsibilities:

• Work within the Molecular Genetics team on experimental design, execution, and research associate training in order to generate large-scale single cell transcriptome datasets.

• Work with Modeling, Analysis and Theory team to timely and iteratively analyze single cell data from the internal single cell transcriptomics pipeline and facilitate generation of cell type taxonomy.

• Design and execute validation and follow-up experiments to place the transcriptomics results in the neurobiological context.

• Write and publish manuscripts, grant progress reports and grant applications.

• Present work internally and externally at conferences.

• Evaluate new single cell RNA-seq platforms and techniques.

• Work with Electrophysiology and Neuroanatomy teams to facilitate data organization and integration in an effort to create multimodal neuronal taxonomy.

Basic Qualifications

  • Ph.D. in life sciences or computational biology (e.g., Neuroscience, Genomics, Genetics, or related field).
  • Knowledgeable in genomic data generation from primary tissues (rodent handling, dissection, single cell collection, molecular biology, and next generation sequencing).
  • Knowledgeable about developmental neurobiology and systems neurobiology
  • Knowledgeable about RNA-seq, ATAC-seq and/or ChIP-seq data
  • Proficiency in R and Linux shell scripting.

Preferred Qualifications

  • 2+ years of experimental experience in genomic data generation from primary tissues (rodent handling, dissection, single cell collection, molecular biology, and next generation sequencing).
  • 2+ years of experience working in a rodent model system studying a neurobiological problem in vivo (e.g., developmental neurobiology, systems neurobiology).
  • 2+ years of computational experience working with RNA-seq, ATAC-seq and/or ChIP-seq data, preferably at the single cell level.
  • Ability to develop, test, implement, and share new experimental and computational tools quickly, in an iterative manner, after feedback from experimental, data production, and analysis teams.
  • Experience with additional programming languages (Perl, Python, Matlab) preferred.
  • Exceptional oral and written communication skills.
  • Ability to work independently as well as part of a team to meet aggressive timelines in a collaborative environment.
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