Key Responsibilities:

80% Perform statistical and bioinformatics analysis:

Research Support: Assist Dr. Vivek in conducting original research by analyzing high-dimensional omics, imaging, and phenotypic data, adhering to best practices such as staying current with literature, tool benchmarking, and code sharing through GitHub.
Data management: Wrangle, clean, structure, and store large datasets from investigators efficiently.
System Development: Help build, populate, and maintain a searchable system for storing raw omics and imaging data, sample metadata, data generation and processing provenance, and custom analysis results.
Workflow Implementation: Assist in implementing scalable, high-performance workflows to support the research community with advanced analytical techniques and disseminate best practices.
Best Practices: Implement best practices for the representation and analysis of omics, imaging, and integrative data for machine learning prediction models and data visualizations.
10% Collaboration, documentation and presentation of research findings:


Documentation and Support: Provide detailed documentation and user support to enable computational researchers to access and re-use analysis pipelines effectively.
Offer processed data and technical support to biostatisticians and computational scientists, identifying and addressing technical factors in data generation and processing to facilitate biological conclusions.
Collaboration: Collaborate with investigators to understand and clarify requests, document requirements, communicate ongoing work, interpret results, and foster a supportive research community. Engage with team members to build, publish, and re-use high-performance open-source code.
10% Manuscript preparation and publication support:


Perform literature reviews for manuscript preparation
Assist with the preparation of materials for presentations and publications, focusing on data visualization, statistical analysis results, and interpretation.
Help create visually appealing and informative publishable quality charts, graphs, and slides.
Qualifications
All required qualifications must be documented on application materials.

Required Qualifications:

Education and Experience:
Master’s degree in Computational Biology, Data Science, Biostatistics, Public Health or a related field and two years of experience, or
BS/BA in Computational Biology, Biotatistics, or a related field and four years of experience.
Programming Skills: Demonstrated skills in a high-level programming language, preferably SAS for data management and statistical analysis, R or Python for data analysis and machine learning models and experience with Linux
Statistical Understanding: Basic understanding of statistics and its applications to biomedical science.
Data Management: Experience with structured data storage and multi-component data processing systems.
Omics/Imaging Data: Experience with architecture or tools for managing “omics” or imaging data.
Multitasking: Ability to prioritize multiple tasks effectively.
Communication Skills: Excellent communication, analytical, and organizational skills, both written and verbal.
Teamwork and Independence: Ability to work independently and as part of a team, demonstrating collaborative problem-solving skills.

Preferred Qualifications:


Demonstrated ability in research related to genomic analysis, machine learning, or image analysis, which may include experience with next-generation sequencing such as RNA-seq, Whole genome sequencing etc. and microarray-based DNA methylation profiling, and multiplexed proteomics platform.
Pay and Benefits
Pay Range: $78,000 - 85,000 depending on education/qualifications/experience
Time Appointment: 75%-100% Appointment
Position Type: Civil-Service & Non-Faculty Labor Represented Staff
Please visit the Office of Human Resources website for more information regarding benefit eligibility.