Computational Biologist (Researcher 4)

University of Minnesota-Twin Cities

Twin Cities, MN

ID: 7249890
Posted: May 31, 2024
Application Deadline: Open Until Filled

Job Description

Key Responsibilities:

80% Perform statistical and bioinformatics analysis:

• Research Support: Partner with Dr. Vivek in conducting original research by leveraging platform-based tools and biological insights to analyze 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 Handling: 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: Implement 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:

• Team Collaboration: Work collaboratively across labs to manage and develop tools and pipelines, supporting investigator discoveries and scholarly work.
• Documentation and Support: Provide detailed documentation and user support to enable computational researchers to access and re-use analysis pipelines effectively.
• Collaborative Coding: Engage with team members to build, publish, and re-use high-performance open-source code.
• Software Development: Contribute to software development using structured software engineering best practices, ensuring robust and reliable tools.
• Technical Support: 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.
• Investigator Collaboration: Collaborate with investigators to understand and clarify requests, document requirements, communicate ongoing work, interpret results, and foster a supportive research community.

10% Manuscript preparation and publication support:

• Prepare materials for presentations and publications, focusing on data visualization, statistical analysis results, and interpretation.
• Create visually appealing and informative publishable quality charts, graphs, and slides.

This position is hybrid with at least three days a week in the office. Our office is located on the West Bank of Minneapolis's campus.

Comp range: $78,000 - 85,000

Qualifications
All required qualifications must be documented on application materials.

Required Qualifications:

Education and Experience:
Master’s degree in Computational Biology, Data Science, Statistics, or a related field and two years of experience, or
BS/BA in Computational Biology, Bioinformatics, Statistics, or a related field and four years of experience.
Programming Skills: Demonstrated skills in a high-level programming language, preferably Python or R, and SAS for data management and statistical analysis and experience with Linux or Unix environments.
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.