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Medical Image Annotation Jobs in Chicago, IL (NOW HIRING)

Medical Image Annotation information

See Chicago, IL salary details

$15

$38

$59

How much do medical image annotation jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for medical image annotation in Chicago, IL is $38.42, according to ZipRecruiter salary data. Most workers in this role earn between $29.71 and $47.79 per hour, depending on experience, location, and employer.

What is medical image annotation?

Medical image annotation is the process of labeling or marking specific structures, regions, or abnormalities in medical images such as X-rays, CT scans, or MRIs. These annotations are crucial for training artificial intelligence (AI) models to assist in diagnostics, research, and treatment planning. Expert annotators, often with medical backgrounds, use specialized software to ensure accuracy and consistency. This work helps improve the performance of AI systems in identifying diseases and supporting healthcare professionals.

What are some common challenges faced by professionals in medical image annotation roles, and how can they be addressed?

Medical image annotation professionals often encounter challenges such as interpreting complex or ambiguous images, ensuring consistency across annotations, and keeping up with evolving medical guidelines. To address these challenges, many teams implement standardized protocols, regular training sessions, and peer review systems to maintain accuracy and reliability. Collaboration with radiologists and other medical experts is also common, allowing annotators to clarify uncertainties and improve the quality of annotations over time.

What is the difference between Medical Image Annotation vs Medical Data Labeling?

AspectMedical Image AnnotationMedical Data Labeling
Required CredentialsBasic understanding of medical imaging, attention to detailSimilar, often no formal certification needed
Work EnvironmentMedical imaging platforms, annotation toolsData management systems, labeling software
Industry UsageHealthcare, medical AI developmentHealthcare, medical AI, data analysis
Search & Comparison IntentYes, often compared for AI training rolesYes, related but broader in data types

Medical Image Annotation involves marking specific regions or features in medical images like X-rays or MRIs to train AI models. Medical Data Labeling encompasses annotating various medical data types, including images, text, and reports. While both roles support medical AI development, Image Annotation is specialized in visual data, whereas Data Labeling covers a wider range of medical information.

What are the key skills and qualifications needed to thrive as a Medical Image Annotation Specialist, and why are they important?

To excel as a Medical Image Annotation Specialist, you need a solid understanding of medical imaging modalities, anatomy, and basic clinical terminology, often supported by relevant education or experience in healthcare or life sciences. Familiarity with annotation software, image processing tools, and sometimes specialized platforms like DICOM viewers is typically required. Attention to detail, precision, and effective communication are crucial soft skills for ensuring accuracy and collaborating with clinical or research teams. These competencies are vital because high-quality, accurate annotations directly impact the development of AI models and the reliability of diagnostic tools in healthcare.
What job categories do people searching Medical Image Annotation jobs in Chicago, IL look for? The top searched job categories for Medical Image Annotation jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Medical Image Annotation jobs? Cities near Chicago, IL with the most Medical Image Annotation job openings:
Infographic showing various Medical Image Annotation job openings in Chicago, IL as of July 2026, with employment types broken down into 6% As Needed, 83% Full Time, 6% Part Time, 3% Temporary, and 2% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $79,919 per year, or $38.4 per hour.
Postdoctoral Scholar (Goldstein Lab)

Postdoctoral Scholar (Goldstein Lab)

Northwestern University

Evanston, IL • On-site

$61K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Northwestern University rating

7.8

Company rating: 7.8 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

204th of 612 rated colleges and universities


Job description

Department: MED-Pathology
Salary/Grade: RES/
The minimum pay for this position is $61,000 in alignment with departmental equity and market data
Who we are: A small lab dedicated to improving maternal-child outcomes through understanding of the placenta.
(wait, what's a placenta?) An organ that develops in pregnancy that supports fetal survival and growth. Most problems in pregnancy are caused by the placenta or leave a signature that we can study.
What we do: Our major techniques are ML analysis of whole slide placental histology images and analysis of spatial multiplex data (transcriptomics, IF). We also use medical informatics data for outcomes. Goldstein lab space is dry, but we work with collaborators and core labs to acquire data.
  • Chou et al., Quantitative Modeling to Characterize Maternal Inflammatory Response of Histologic Chorioamnionitis in Placental Membranes. Am J Reprod Immunol. 2024 Oct;92(4):e13944. doi: 10.1111/aji.13944.
  • Ayad et al., Deep learning for fetal inflammatory response diagnosis in the umbilical cord. Placenta. 2025 Jun 26;167:1-10. doi: 10.1016/j.placenta.2025.04.013
The project: Stillbirth is loss of pregnancy after 20 (of 40) weeks gestation. It occurs in ~1% of pregnancies, and the cause is unknown in around half of cases. The goal of the project is to build multimodal models that intake clinical data and whole slide images and yield a classification of the cause of stillbirth. The position is on an NIH-funded R01 in year 2 of 5.
This fellow will collaborate with an interdisciplinary team of machine learning, image analysis, and software engineering experts and will have access to data and resources to develop, validate, and translate their work. Candidates must have strong computational skills and a PhD with research experience in ML or computationally intensive biology. Preference will be given to recent graduates of US institutions or who are currently employed in the US and who are immediately eligible to work.
The Division of Computational Pathology at Northwestern was formed to improve pathology practice and research through the application of AI techniques. We have created a research environment where pathologists and computational scientists from different backgrounds collaborate to develop AI tools and translate them into clinical practice. We maintain an institutional repository containing >100,000 images linked to diagnostic and clinical data, a dedicated computing cluster, and a platform for image viewing, annotation, and data management. Our hospital system is implementing digital pathology for clinical operations and has experience with operationalizing AI tools.
This position is supervised by Dr. Jeffery A. Goldstein and the primary appointment will be in the department of pathology on the Downtown Chicago Streeterville campus. Northwestern has a vibrant AI research community, with the Institute of Augmented Intelligence in Medicine and AI@NU. The fellow will have opportunities to collaborate with Lee Cooper, head of the division of computational pathology, as well as other faculty in the Department of Pathology, Prentice Women's Hospital, the Lurie Cancer Center, and the McCormick School of Engineering.
Principle Responsibilities:
  • Develop methods for analyzing pathology images
  • Management of research datasets
  • Interact with collaborators, other postdocs, and graduate students to achieve project goals
  • Manuscript development
  • Attendance at conferences and symposia where results will be presented in poster or talk formats
Requirements:
  • PhD in computer science, computational biology, bioinformatics or similar.
  • Advanced level of Python programming
  • Experience working with Linux-based systems
Preferred
  • Experience with software optimization and large-scale datasets
  • Experience with Git version control
  • Experience in computer vision and deep learning
  • Experience with medical images
#LI-RM1
Northwestern University is an Equal Opportunity Employer and does not discriminate on the basis of protected characteristics, including disability and veteran status. View Northwestern's non-discrimination statement . Job applicants who wish to request an accommodation in the application or hiring process should contact the Office of Civil Rights and Title IX Compliance. View additional information on the accommodations process .

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