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Medical Image Annotation Jobs in Texas (NOW HIRING)

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Medical Image Annotation information

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 Texas look for? The top searched job categories for Medical Image Annotation jobs in Texas are:
What cities in Texas are hiring for Medical Image Annotation jobs? Cities in Texas with the most Medical Image Annotation job openings:
Infographic showing various Medical Image Annotation job openings in Texas as of June 2026, with employment types broken down into 25% Internship, and 75% Full Time. Highlights an 100% In-person job distribution.
Postdoctoral Fellow - Genitourinary Medical Oncology - Research

Postdoctoral Fellow - Genitourinary Medical Oncology - Research

MD Anderson

Houston, TX

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 6 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 165 frontline employees who took The Breakroom Quiz

33rd of 876 rated healthcare providers


Job description

A postdoctoral position focused on cellular danger response signaling and interaction with the tumor immune microenvironment in renal cell carcinoma is available in the laboratory of Dr. Eric Jonasch. We are looking for highly self-motivated candidates with a recent PhD or MD degree, to investigate the cellular and molecular mechanisms of STING pathway signaling in renal cell carcinoma as well as therapy resistance to targeted therapy and immunotherapy.
To study the cellular and molecular mechanisms of cellular danger response in renal cell carcinoma as well as therapy resistance to chemotherapy, targeted therapy, and immunotherapy.
Successful candidate must be able to design novel projects, create hypothesis-driven experiment, maintain excellent descriptions of experiments performed, standardize and validate new methods and be able to interpret results. Computer skills such as entering data obtained from experiments into graphic and statistics programs as well as the generation of figures after image analysis are essentials. The employee should provide scientific expertise and organizational skills in getting involved in various research projects involving human subject research. Candidate will be responsible for coordinating procedures with collaborators. Other skills include performing technical laboratory duties in accordance with general and/or specific plans. Read, write and edit manuscripts and reports, as well as help with grant writing.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
-Develop capabilities for perform spatial transcriptomic analyses on RCC and VHL disease related samples.
-Develop and expand the ability to perform bioinformatic analyses of single cell and spatial transcriptomic analysis.
-Become proficient in the intersection of tumor immune microenvironment, tumor metabolism, tumor microbiome, disease progression and treatment response in patients with nodal disease.
-Learn metastatic and primary tumor tissue processing and clinical annotation in patients with locally advanced and metastatic disease.
To accomplish the learning objective, the candidate will be matched with GU oncology clinical faculty (Dr. Eric Jonasch as well as translational faculty (Dr. Xiande Liu).
ELIGIBILITY REQUIREMENTS
MD or PhD (recent, within 3 years)
- Prefer candidate to have knowledge of tissue processing for single cell studies, metabolomics, and microbiome studies
- Prefer candidate with skills in clinical database management and clinical specimen annotation.
ADDITIONAL APPLICATION INFORMATION
- Prefer candidate to have knowledge of tissue processing for single cell studies, metabolomics, and microbiome studies
- Prefer candidate with skills in clinical database management and clinical specimen annotation.
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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