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What is remote imaging informatics?

Remote imaging informatics is a specialized field that focuses on managing, analyzing, and sharing medical images and related data using digital information technologies from remote locations. Professionals in this field develop and maintain systems that allow healthcare providers to access, interpret, and store medical images such as X-rays, MRIs, and CT scans securely and efficiently, regardless of physical location. This facilitates faster diagnoses, greater collaboration among medical teams, and improved patient care. Remote imaging informatics is essential for telemedicine and for supporting hospitals and clinics that may not have on-site specialists.

What are the key skills and qualifications needed to thrive as a Remote Imaging Informatics Specialist, and why are they important?

To excel in Remote Imaging Informatics, you need a strong background in medical imaging, IT systems, and data management, often supported by a degree in health informatics, computer science, or a related field. Familiarity with PACS, RIS, DICOM standards, and certifications like CIIP (Certified Imaging Informatics Professional) are typically required. Excellent problem-solving, communication, and collaboration skills are vital for coordinating with radiologists, IT teams, and healthcare providers remotely. These skills are crucial for ensuring seamless integration, secure image management, and optimal support of clinical workflows in distributed healthcare environments.

What are some common challenges faced by professionals in remote imaging informatics, and how can they be addressed?

Professionals in remote imaging informatics often encounter challenges such as maintaining secure and reliable access to large imaging datasets, ensuring smooth communication with on-site clinical teams, and troubleshooting technical issues from a distance. To address these, it's important to be proficient in telecommunication tools and remote troubleshooting techniques, and to stay updated on cybersecurity best practices. Establishing clear communication protocols and collaborating closely with both IT and clinical staff also helps ensure workflow efficiency and high-quality patient care.
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Contingent Summer Research Analyst Intern

Contingent Summer Research Analyst Intern

Arbor Research Collaborative for Health

Ann Arbor, MI • Remote

$27/hr

Full-time

Posted yesterday

Job description

About the Project

The CKD study uses 5 years of structured EHR data from a large private nephrology practice with over 50,000 patients. The study aims to:

  • Build standardized, analysis-ready analytic files (SAFs) spanning 2021–2025
  • Assess feasibility of longitudinal data elements (labs, prescriptions, disease history)
  • Characterize CD patients using contemporary clinical and treatment data
  • Evaluate the availability of specific variables (imaging, genetics, family history) in unstructured clinical records

The intern will be embedded in an active project team that includes biostatisticians, epidemiologists, data scientists, and clinical nephrologists, and will contribute to analytic work from day one.

Key Responsibilities
  • Contribute to construction and QC of longitudinal electronic health record (EHR) analytic files using structured data
  • Conduct descriptive analyses of patient demographics, lab values, medication use, and clinical characteristics
  • Summarize data availability, follow-up patterns, and measurement frequency across CKD subgroups
  • Support feasibility assessments by generating counts, proportions, and distributional summaries
  • Produce clean, well-documented analytic code and contribute to draft tables and figures
  • Participate in biweekly internal team meetings and client meetings, and contribute to written deliverables
Qualifications

Required:

  • Currently enrolled in a graduate program (MPH, MS, PhD, or equivalent) in biostatistics, epidemiology, data science, health informatics, or a related field
  • Proficiency in Python, R, or SAS for data manipulation and descriptive analysis
  • Comfort working with big data – large, messy, real-world datasets
  • Strong attention to detail and ability to write clean, reproducible, well-commented code
  • Ability to work independently with remote supervision
  • Comfort using AI-assisted coding tools (e.g., Claude, GitHub Copilot)

Preferred:

  • Familiarity with EHR data or claims-based data
  • Experience with longitudinal data structures (e.g., repeated lab measurements, time-to-event)
  • Experience with version control (Git)
Position Details
  • Duration: approximately July 1 – August 29, 2026 (flexible start; contingent on contract execution)
  • Hours: full-time (~40 hrs/week) or near full-time
  • Location: fully remote; no travel required
  • Compensation: paid internship (rate commensurate with experience)
  • Supervisor: Brian Bieber, MS, Research Scientist, Data Science
How to Apply

Submit a CV and a brief cover letter (1 page max) describing your relevant experience and availability. Applications will be reviewed on a rolling basis — early submission is strongly encouraged given the July start date.

Pay

$27 USD per hour

Apply