Research Data Analyst 2

$86,000 - $126,000/Yr

Stanford University - Stanford, CA

posted 2 months ago

Full-time - Mid Level
Remote - Stanford, CA
Educational Services

About the position

The Sergiu Pasca Lab and Kevin Kelley Lab, within the Department of Psychiatry & Behavioral Sciences at Stanford University, are seeking a motivated computational bioinformatic scientist to join a highly collaborative environment focused on human neuroscience and neurodevelopmental disease modeling. This position offers a unique opportunity to work at the forefront of research that couples advanced human brain cellular models with innovative computational genomics. The successful candidate will be embedded within an interdisciplinary team and will be responsible for developing novel computational and statistical approaches for analyzing and interpreting large multi-modal sequencing and imaging datasets derived from human neural tissue. In this role, the candidate will develop rigorous and reproducible analytic pipelines for processing and interpreting large datasets generated from single-cell RNA-seq, ATAC-seq, spatial transcriptomics, and electrophysiology data. The environment is designed to foster significant contributions to the understanding of neuropsychiatric disorders, providing the successful applicant with opportunities to grow into a leadership role within academia or industry. The position is hybrid eligible, allowing for a combination of on-site and remote work, and is full-time with regular employee status. The candidate will also be expected to stay up to date with computational bioinformatics best practices and data analysis methods through recent publications, seminars, conferences, and training courses. This role is integral to the lab's mission and will involve close collaboration with experimentalist colleagues, including postdocs, graduate students, and staff, to design and interpret high-dimensional dataset collection and analysis.

Responsibilities

  • Develop lab-wide high-dimensional data initiatives from storage to preprocessing to interpretation.
  • Develop reproducible processing pipelines for single cell RNA-seq, ATAC-seq, multi-omics, spatial transcriptomics, and electrophysiology data.
  • Enable experimentalist colleagues with close collaboration, design, and interpretation of high-dimensional dataset collection and analysis.
  • Present computational efforts at conferences and symposia.
  • Generate peer-reviewed publications with colleagues.
  • Stay up to date with computational bioinformatics best practices and data analysis methods from recent publications, seminars, conferences, and training courses.

Requirements

  • PhD in computational or bioinformatics-related field; alternatively, PhD in biology or neuroscience-related fields with strong computational experience.
  • Strong background in bioinformatics, computational genomics, and statistics, including analysis of high-throughput sequencing data with relevant publication record.
  • Proficiency with high performance computing, database management, and multiple programming languages (e.g. Python, R).
  • Experience working within a UNIX/Linux environment.
  • Excellent communication and team skills and fluency in both spoken and written English.
  • Bachelor's degree and three years of relevant experience or combination of education and relevant experience in a quantitative discipline such as economics, finance, statistics, or engineering.

Nice-to-haves

  • Experience in a laboratory or field setting.
  • Familiarity with additional programming languages or data analysis tools.

Benefits

  • Hybrid work arrangement
  • Competitive salary range of $86,000 to $126,000 per annum
  • Opportunities for professional development and growth within academia or industry
  • Access to Stanford University's resources and facilities.
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