Bioinformatics Analyst 2

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive.

Job Location (Full Address):

601 Elmwood Ave, Rochester, New York, United States of America, 14642

Opening:

Worker Subtype:

Regular

Time Type:

Full time

Scheduled Weekly Hours:

40

Department:

400911 Ctr Musculoskeletal Research

Work Shift:

UR - Day (United States of America)

Range:

UR URG 113

Compensation Range:

$77,600.00 - $116,400.00

Responsibilities:

Contributes to the scientific analysis and interpretation of data generated by multiple musculoskeletal research projects by organizing, overseeing, and directing the work of assigned Biomechanical Testing Core staff and trainees. Initiates, monitors, and evaluates the progress, methodological quality, and scientific value of projects and associated datasets. Exercises independent scientific and technical judgment in experimental design, development of analytical methods, interpretation of findings, and resolution of complex research problems.

Responsible for quality control of raw biomechanical data and assists investigators with analysis from data generation through publication. Integrates mechanical testing, imaging, specimen geometry, and other experimental datasets into quantitative models of tissue structure and function. Develops, validates, and maintains computational workflows for on-premises and cloud processing.

Establishes and maintains collaborative relationships with investigators, research cores, institutional computing teams, and external partners. Provides technical supervision, research consultation, and training, and develops educational materials related to specialized experimental and computational methods.

ESSENTIAL FUNCTIONS

• Independently collaborates with investigators to define research questions, experimental designs, testing strategies, analytical approaches, deliverables, and timelines. Independently evaluates the feasibility and limitations of proposed methods, recommends appropriate controls and quality criteria, and coordinates concurrent projects. Monitors milestones, interprets emerging findings, and recommends methodological changes or follow-up experiments in consultation with investigators.
• Develops and applies computational and statistical methods to process, analyze, visualize, and interpret biomechanical data. Establishes reproducible procedures for signal processing, identification of testing artifacts, calculation of structural and material properties, and comparison of experimental groups. Integrates mechanical outcomes with imaging, geometry, specimen metadata, and other relevant measurements. Evaluates analytical assumptions and communicates findings and limitations through investigator consultations, reports, figures, manuscripts, abstracts, and grant materials.
• Designs, implements, tests, documents, and maintains reusable software and automated workflows for instrument-data ingestion, quality control, analysis, visualization, and reporting. Uses scientific programming languages, open-source tools, and version control to support reproducibility and reliable deployment. Collaborates with institutional research computing and information technology personnel to develop workflows for local and approved cloud infrastructure, including appropriate storage, access, and computational resources.
• Establishes and maintains standards for raw and processed data, specimen identifiers, metadata, analytical records, and workflow documentation. Develops procedures that preserve traceability from specimen preparation and instrument output to reported results. Oversees data organization, storage, backup, retrieval, and access in accordance with institutional requirements. Reviews data completeness and quality, investigates discrepancies, and implements corrective actions.
• Provides technical training, supervision, and consultation to the CMSR research groups, assigned Biomechanical Testing Core staff, students, and trainees. Develops instructional materials, digital manuals, standard operating procedures, and example workflows. Establishes and maintains collaborative relationships with multiple stakeholders within and external to the University, including investigators, research cores, and institutional computing teams.
• Oversees scheduling, specimen intake and tracking, project records, supply and fixture inventories, and service documentation supporting core operations and internal billing. Establishes and monitors instrument performance and calibration checks. Troubleshoots equipment and software problems and coordinates maintenance, repairs, upgrades, and vendor support. Evaluates emerging technologies and recommends improvements based on scientific needs, performance, reliability, and resource requirements.
• Other duties as assigned

MINIMUM EDUCATION & EXPERIENCE

• Bachelor's degree required in biomedical engineering, mechanical engineering, biomechanics, or materials science preferred
• 3 years of relevant experience required
• Master's degree preferred
• Or equivalent combination of education and experience
• Experience with Azure/AWS or other cloud platform development/deployment required
• Experience with statistical programming and data visualization using R/Bioconductor and UNIX/Linux programming required
• Experience with interface, networking, and data warehousing technologies, as well as design, relational database technologies, and performance tuning required

KNOWLEDGE, SKILLS AND ABILITIES

• Proven track record executing multiple work streams and producing consistent results required
• Able to create novel techniques, programs and systems by innovation or by extracting/synthesizing features or elements from other systems, databases and/or programs at all phases inception, design, testing, implementation, evaluation and future progression and development required
• Ability to create a cascade of interrelated experiments, programs and/or systems that execute, analyze and construct upon the previous and in scientific succession required
• Web interface, design and development experience, Javascript, Python/Flask or related programming experience, including source control tools such as GIT preferred
• Competency with Python, JAVA, Perl, C++, and Cloud computing required
• Knowledge of basic statistics, linear model building, principal component analysis, and factor analysis preferred
• Experience conducting biomechanical, mechanical, materials, or tissue testing, including experimental planning, specimen preparation, instrument operation, troubleshooting, and quantitative analysis preferred
• Experience with instrument-data interfaces, structured data storage, relational databases or comparable research data systems, and integration of heterogeneous datasets preferred
• Demonstrated ability to develop and validate new experimental methods, analytical programs, or research systems through design, testing, implementation, evaluation, and improvement preferred
• Demonstrated ability to manage multiple projects, meet milestones, maintain rigorous documentation, and deliver reliable results preferred
• Experience providing technical training, coordinating the work of others, and communicating complex methods and findings to collaborators with varied technical backgrounds preferred
• Ability to handle animal tissues, human cadaveric materials, and other biological specimens in accordance with applicable institutional requirements and approved protocols preferred
• Demonstrated proficiency in scientific programming and data visualization using either Python, R, MATLAB, or comparable platforms, including development of automated and reproducible analytical workflows preferred
• Experience with statistical programming and data visualization using R/Bioconductor and LLM preferred
• Knowledge of basic statistics, linear model building, principal component analysis, and factor analysis preferred

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