Situated in Stanford’s highly dynamic research environment the Curtis Laboratory (http://med.stanford.edu/curtislab.html), led by Christina Curtis, PhD, is seeking a bioinformatician/Research Data Analyst 3 to join the Cancer Computational and Systems Biology group. The Curtis Laboratory is administratively situated within the Stanford Cancer Institute and is integrated within Stanford University and the School of Medicine’s Departments of Medicine (Oncology) and Genetics. The SCI is part of a Comprehensive National Cancer Institute Cancer Center for cross-disciplinary research in cancer biology involving researchers from oncology, radiobiology, computer science, genetics, statistics, and basic/translational clinical research. Our research couples state-of-the-art computational and experimental techniques to define novel therapeutic targets and biomarkers and to characterize tumor evolution.
The successful candidate will be part of an interdisciplinary research team developing novel technological and methodological approaches to improve the diagnosis, treatment and earlier detection of cancer. He/she will analyze and interpret large sequencing datasets by applying and developing bioinformatics and statistical methods whole genome/exome sequencing, RNA-seq, ATAC-seq, single cell, and circulating tumor DNA (ctDNA) data. The successful candidate will interact closely with other computational and experimental biologists and clinicians to test, validate, and refine hypotheses. This is a fantastic opportunity for a motivated bioinformatician, computational genomicist to join a dynamic team with significant opportunities for scholarship and leadership.
Duties include:
Lead and own organization-wide data initiatives (e.g. models, frameworks, platforms, dashboards).
Supervise, coach and mentor a high-performing team of analysts.
Identify, leverage and partner with external firms.
Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
Determine additional data collection and reporting requirements. Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
Test prototype software and participate in approval and release process for new software.
Provide documentation based on audit and reporting criteria to investigators and research staff.
Work with lab members to analyze biomedical data and address scientific problems with bioinformatics techniques
Design, develop, and operate computational pipelines for the analysis of sequencing data.
Install, maintain, evaluate third party software packages.
Manage and archive large data sets from next-generation sequencing experiments.
Maintain detailed records of all analyses.
Present results and progress updates at lab meetings and make presentations to experimental and scientific collaborators.
Attend seminars, lectures, and training courses to learn new bioinformatic skills and remain up to date with the cancer genomics field.
* - Other duties may also be assigned
DESIRED QUALIFICATIONS:
Bachelor’s degree (or higher) in Bioinformatics, Computer Science or a related field with two years of relevant experience
PhD in bioinformatics-related field
Strong background in bioinformatics and biostatistics, including analysis of high-throughput sequencing data
Experience working within a UNIX/Linux environment
Fluency in programming languages such as Perl, Python, Java, R, C, Matlab; MySQL
Excellent communication and team skills and fluency in both spoken and written English
Familiarity with machine learning, information theory and signal processing.
Experience with algorithm development
Familiarity with basic molecular biology
Background in cancer biology
Expertise in bioinformatics, computational genomics, evolutionary biology, accompanied by a relevant publication record.
Proficiency with high performance computing and multiple programming languages (C, Python, R).
Experience with high-throughput genome sequence data (WES, WGS, RNA-seq, ATAC-seq)
A background in evolutionary biology and familiarity with phylogenetics techniques.
Experience with high-performance computing, database management.
EDUCATION & EXPERIENCE (REQUIRED):
Bachelor's degree and five years or more 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):
Ability to direct the work of others, for jobs requiring supervision.
Relevant subject matter knowledge.
Substantial experience with MS Office and analytical programs.
Excellent writing and analytical skills.
Ability to prioritize workload.
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.
WORK STANDARDS:
Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu.
This hybrid or remote role is open to candidates anywhere in the United States. Stanford University has five Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range for this position is $88,000 to $159,000 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.
