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Data and AI Researcher II, Department of Basic Medical Sciences (College of Medicine - Phoenix)

Company:
The University of Arizona
Job Location:
Tucson, 85724
Category:
Laboratory and Research
Type:
Full-Time

Posting Number: req25846

Department: COM Phx Biomedical Informatics

Location: Greater Phoenix Area

Address: Phoenix, AZ USA

Position Highlights

The University of Arizona College of Medicine - Phoenix (COM-P) is seeking a highly motivated candidate for the full-time position of Data and AI Researcher II in Dr. Peipei Ping's laboratory. Our lab develops integrative omics and AI-driven data science approaches to uncover how genes, proteins, and their dynamic interactions shape cardiovascular function and disease, with the goal of transforming large-scale biological and clinical data into actionable insights for diagnosis, treatment, and scientific discovery. The ideal candidate should have a strong background in computational biology, data science, and/or omics analysis, with experience in large-scale biomedical data integration. The individual will develop and apply analytical and machine learning methods to interrogate complex multi-omics, imaging, and clinical datasets, contributing to research in cardiovascular systems biology and precision medicine. The Data and AI Researcher II will benefit from the highly collaborative and interdisciplinary environment within Dr. Peipei Ping's lab and its broader national partnerships in AI-driven biomedical research.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please .

Duties & Responsibilities

  • Analyze multi-omics, imaging, and clinical datasets using established analytical and statistical methods.
  • Contribute to ongoing studies in cardiovascular systems biology, including exposure to proteomics, transcriptomics, and integrative data analysis approaches.
  • Interpret results and collaborate in preparing summaries, presentations, and draft materials for publications.
  • Review and apply existing computational workflows to support reproducible and well-documented data analysis.
  • Provide support for the use and maintenance of computational pipelines for multi-modal biomedical data.
  • Apply existing machine learning and data analysis methods under guidance from senior team members.
  • Work with the PI and team to improve organization, usability, and documentation of analytical tools and workflows.
  • Document workflows, software usage, and standard operating procedures (SOPs) to support reproducibility and team knowledge sharing.
  • Collaborate with interdisciplinary teams, including researchers in computational biology, clinical research, and data science.
  • Contribute to preparing reports, manuscripts, and grant-related materials, including coordination and formatting support.
  • Present summaries of work and project updates in lab meetings and collaborative settings, with guidance as needed.

Knowledge, Skills, and Abilities:

  • Ability to communicate in a clear, concise manner orally and in writing.
  • Detailed oriented, conscientious, and able to follow instructions.
  • Knowledge of the principles and techniques of the subject discipline.
  • Knowledge of modern research methods, data collection and analyses.
  • Skill in analyzing and evaluating data.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

Minimum Qualifications

  • Bachelor's degree or equivalent advanced learning attained through professional level experience required.
  • Three (3) years of relevant experience, or equivalent combination of education and work experience

Preferred Qualifications

  • Bachelor's degree in a field of science or similar degree.
  • Previous research experience (internship, independent study).
  • Experience with multimodal biomedical data integration (e.g., omics + imagine + text data).
  • Familiarity with foundation models, generative AI, or clinical language models.
  • Experience with natural language processing (NLP) pipelines and techniques.

FLSA: Exempt

Full Time/Part Time: Part Time

Number of Hours Worked per Week: Varies

Job FTE: 0.80

Work Calendar: Fiscal

Job Category: Research

Benefits Eligible: Yes - Full Benefits

Rate of Pay: $75,540 - $98,201

Compensation Type: salary at 1.0 full-time equivalency (FTE)

Grade

10

Compensation Guidance

The Rate of Pay Field represents the University of Arizona's good faith and reasonable estimate of the range of possible compensation at the time of posting. The University considers several factors when extending an offer, including but not limited to, the role and associated responsibilities, a candidate's work experience, education/training, key skills, and internal equity.

The Grade Range represent a full range of career compensation growth over time. The university offers compensation growth opportunities within its career architecture. To learn more about compensation, please review our and our .

Career Stream and Level

PC2

Job Family

Research & Data Analysis

Job Function

Research

Type of criminal background check required: Name-based criminal background check (non-security sensitive)

Number of Vacancies: 1

Contact Information for Candidates

Office of Human 四虎影视, Talent Acquisition

talent@arizona.edu

Open Until Filled: Yes

Documents Needed to Apply: Resume

Notice of Availability of the Annual Security and Fire Safety Report

In compliance with the Jeanne Clery Campus Safety Act (Clery Act), each year the University of Arizona releases an for each of the University's campuses. These reports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures.
Paper copies of the Reports can be obtained by contacting the University Compliance Office at cleryact@arizona.edu.

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