The intern will participate in imaging biomarker research projects focused on MRI, CT, AI modeling ... data, image review and annotation, extraction of quantitative imaging features, support for AI ...
New
The intern will participate in imaging biomarker research projects focused on MRI, CT, AI modeling ... data, image review and annotation, extraction of quantitative imaging features, support for AI ...
New
The intern will assist with retrospective and prospective imaging studies to identify and validate ... and clinical data, image review and annotation, extraction of quantitative imaging features ...
New
The intern will assist with retrospective and prospective imaging studies to identify and validate ... and clinical data, image review and annotation, extraction of quantitative imaging features ...
New
Data Annotation Intern information
What is the difference between Data Annotation Intern vs Data Labeling Specialist?
| Aspect | Data Annotation Intern | Data Labeling Specialist |
|---|---|---|
| Credentials | Typically pursuing or recent graduate in related field | Relevant experience or certifications in data labeling |
| Work Environment | Internship setting, often in tech or AI companies | Full-time or freelance roles in data annotation projects |
| Industry Usage | Common in tech, AI, and machine learning industries | Used across similar industries for data preparation |
| Job Focus | Learning and assisting with data annotation tasks | Performing detailed data labeling and quality control |
While both roles involve working with data annotation, a Data Annotation Intern is typically a beginner or student gaining experience, whereas a Data Labeling Specialist is a more experienced professional focused on precise data labeling tasks. Interns often work under supervision, while specialists handle independent projects.
What is a data annotation intern?
A data annotation intern is a temporary position where individuals label or categorize data, such as images, text, or videos, to help train machine learning models. The role typically involves using annotation tools and requires attention to detail to ensure data accuracy and quality.
Is data annotation real or fake?
Data annotation is a legitimate job role involving labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and often involves using specialized tools; the work is real and essential for AI development.
Does data annotation actually pay?
Data annotation internships and entry-level roles typically offer compensation, with pay rates varying based on the company, location, and experience. Many companies pay hourly or project-based wages, and some may provide stipends or bonuses for completing annotation tasks using tools like labeling software. It is common for data annotation jobs to be paid positions, especially when performed on a regular or full-time basis.
Is it hard to get hired for data annotation?
Getting hired as a data annotation intern generally depends on the company's requirements, but the process is often straightforward with basic computer skills and attention to detail. Many positions are entry-level and do not require extensive experience or certifications, making them accessible to beginners. However, strong accuracy and familiarity with annotation tools can improve chances of selection.
What are some common challenges faced by Data Annotation Interns and how can they be overcome?
Data Annotation Interns often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially when guidelines evolve or when dealing with ambiguous cases. To overcome these challenges, it's important to frequently review annotation guidelines, communicate proactively with supervisors or team members for clarification, and participate in regular quality checks. Collaborating with experienced annotators and leveraging feedback provided during peer reviews can also help interns improve their accuracy and efficiency.
What are Data Annotation Interns?
Data Annotation Interns are entry-level professionals who assist in labeling and categorizing data, such as images, audio, or text, to help train machine learning models. Their work is crucial for ensuring that AI systems can accurately interpret and process various types of data. Interns typically use specialized software tools to annotate data according to specific guidelines, and they may also help with data quality checks. This position is ideal for those interested in gaining experience in artificial intelligence, data science, or related fields.
What are the key skills and qualifications needed to thrive as a Data Annotation Intern, and why are they important?
To thrive as a Data Annotation Intern, you need strong attention to detail, basic computer literacy, and familiarity with data labeling concepts, often supported by a background in computer science or related fields. Familiarity with annotation tools like Labelbox, Supervisely, or CVAT and understanding of data formats such as JSON or XML are typically required. Effective communication, time management, and the ability to follow complex guidelines are important soft skills for this role. These skills ensure high-quality, consistent data labeling, which is crucial for training accurate machine learning models.
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What are popular job titles related to Data Annotation Intern jobs in Texas? For Data Annotation Intern jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Annotation Intern jobs in Texas look for? The top searched job categories for Data Annotation Intern jobs in Texas are:
What cities in Texas are hiring for Data Annotation Intern jobs? Cities in Texas with the most Data Annotation Intern job openings:
MD Anderson Cancer Center rating
8.4
Based on 168 frontline employees who took The Breakroom Quiz
30th of 880 rated healthcare providers
Job description
We are seeking a highly motivated Research Intern with a background in biological sciences to work in the Department of Thoracic Imaging at MD Anderson Cancer Center. The intern will participate in imaging biomarker research projects focused on MRI, CT, AI modeling, and tumor response assessment in patients with cancer.
The intern will assist with retrospective and prospective imaging studies to identify and validate imaging biomarkers that may improve diagnosis, prognosis, and assessment of treatment response. Responsibilities may include collection and organization of imaging and clinical data, image review and annotation, extraction of quantitative imaging features, support for AI-based projects, assistance with RECIST and other response assessment methods, and collaboration with radiologists and research staff on data interpretation, abstract development, and manuscript preparation.
This position provides exposure to translational imaging research and to the growing role of quantitative imaging biomarkers in precision oncology.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
1. Learn the principles of imaging biomarkers in oncologic imaging, including their use in diagnosis, prognosis, and treatment response assessment.
2. Gain experience with MRI- and CT-based imaging research workflows, including image review, annotation, and data organization.
3. Understand the basics of AI modeling, quantitative image feature extraction and correlation with clinical outcomes.
4. Develop familiarity with response assessment methods such as RECIST and other imaging-based treatment response criteria.
5. Participate in multidisciplinary imaging research involving radiologists, clinicians, and research staff.
6. Build skills in scientific communication through data presentation, abstract preparation, and manuscript support.
ELIGIBILITY REQUIREMENTS
The ideal candidate will have recently (within one year) been awarded a bachelor's or master's degree in biological sciences or a related field. Prior research experience is preferred but not required.
POSITION INFORMATION
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
The intern will assist with retrospective and prospective imaging studies to identify and validate imaging biomarkers that may improve diagnosis, prognosis, and assessment of treatment response. Responsibilities may include collection and organization of imaging and clinical data, image review and annotation, extraction of quantitative imaging features, support for AI-based projects, assistance with RECIST and other response assessment methods, and collaboration with radiologists and research staff on data interpretation, abstract development, and manuscript preparation.
This position provides exposure to translational imaging research and to the growing role of quantitative imaging biomarkers in precision oncology.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
1. Learn the principles of imaging biomarkers in oncologic imaging, including their use in diagnosis, prognosis, and treatment response assessment.
2. Gain experience with MRI- and CT-based imaging research workflows, including image review, annotation, and data organization.
3. Understand the basics of AI modeling, quantitative image feature extraction and correlation with clinical outcomes.
4. Develop familiarity with response assessment methods such as RECIST and other imaging-based treatment response criteria.
5. Participate in multidisciplinary imaging research involving radiologists, clinicians, and research staff.
6. Build skills in scientific communication through data presentation, abstract preparation, and manuscript support.
ELIGIBILITY REQUIREMENTS
The ideal candidate will have recently (within one year) been awarded a bachelor's or master's degree in biological sciences or a related field. Prior research experience is preferred but not required.
POSITION INFORMATION
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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About MD Anderson Cancer Center
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Industry
Health care and social assistance
Company size
10,000+ Employees
Headquarters location
Houston, TX, US
Year founded
1944