Research Data Analyst 2

Stanford University • FULL_TIME • Stanford, California • 1m ago

The Sergiu Pasca Lab and Kevin Kelley Lab, within the Department of Psychiatry & Behavioral Sciences at Stanford University, have an exciting and unique opportunity for a motivated computational/bioinformatic scientist interested in joining a highly collaborative environment at the forefront of human neuroscience and neurodevelopmental disease modeling. Our research couples advanced human brain cellular models with innovative computational genomics to address fundamental questions on the neurobiological mechanisms of psychiatric disease. The successful candidate will be embedded within an interdisciplinary team and will develop novel computational and statistical approaches for analyzing and interpreting large multi-modal sequencing and imaging based datasets from human-derived neural tissue. They 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. We offer an exciting environment where the successful applicant can make significant contributions to the advancement of our understanding of neuropsychiatric disorders and grow into a leader within academia or industry.

Duties include:

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, electrophysiology data or combinations of these technologies.
Enable experimentalist colleagues (i.e. postdocs, graduate students, staff) with close collaboration, design, and interpretation of high-dimensional dataset collection and analysis.
Presenting computational efforts at conferences and symposia.
Generation of peer-reviewed publications with colleagues.
Staying up to date with computational/bioinformatics best practices and data analysis methods from recent publications, seminars, conferences, and training courses.

* - Other duties may also be assigned

DESIRED QUALIFICATIONS:

PhD in computational or bioinformatics-related field; Alternatively, PhD in biology/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

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

Relevant subject matter knowledge.
Substantial experience with high performance computing, database management, and multiple programming languages (e.g. Python, R).
Experience working within a UNIX/Linux environment.
Excellent writing and analytical skills.
Ability to prioritize workload.
Substantial experience with MS Office and analytical programs.

PHYSICAL REQUIREMENTS*:

·Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.

·Occasionally use a telephone.

·Rarely writing by hand.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

·Some work may be performed in a laboratory or field setting.

·This position is based on the Stanford main campus with the option of telecommuting/hybrid schedule subject to operational needs.

The expected pay range for this position is $86,000 to $126,000 per annum.Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position.The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

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