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Internship Medical Data Annotation Jobs in Connecticut

... forecasting, data analytics, competitive intelligence, healthcare trend analytics and tracking ... Monitoring and forecasting medical cost trends * Regulatory filings * New product development and ...

... forecasting, data analytics, competitive intelligence, healthcare trend analytics and tracking ... Monitoring and forecasting medical cost trends * Regulatory filings * New product development and ...

... forecasting, data analytics, competitive intelligence, healthcare trend analytics and tracking ... Monitoring and forecasting medical cost trends * Regulatory filings * New product development and ...

Past internship or work experience with an actuarial firm doing data analysis is preferred ... Medical, Dental and Vision - Coverage for employees, dependents, and domestic partners. * Employee ...

Associate Data Scientist

Stamford, CT · On-site +1

$62K - $63K/yr

... internships, or research. * Experience with Python, SQL, statistical analysis, and databases ... Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance ...

New

Associate Data Scientist

Stamford, CT · On-site

$62K - $63K/yr

... internships, or research. * Experience with Python, SQL, statistical analysis, and databases ... Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance ...

New

... medical microbiology. * Assess the impact of antibiotics and other agents on microbial populations ... Document experimental findings and processes with a focus on clarity for AI training data.

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Internship Medical Data Annotation information

What is the difference between Internship Medical Data Annotation vs Medical Data Labeling Specialist?

AspectInternship Medical Data AnnotationMedical Data Labeling Specialist
CredentialsTypically students or entry-level with basic knowledgeRelevant certifications or experience in data annotation
Work EnvironmentInternship programs, often in healthcare or tech companiesFull-time or part-time roles in healthcare tech firms
Industry UsageUsed for training and educational purposes, entry-level projectsOperational roles focusing on data accuracy and labeling

Internship Medical Data Annotation roles are usually entry-level positions designed for students or newcomers to gain experience, often within internship programs. Medical Data Labeling Specialists are more experienced roles focused on precise data annotation for AI training, requiring relevant skills or certifications. While both involve working with medical data, internships are more educational, whereas specialists handle ongoing, professional data labeling tasks.

What are the most commonly searched types of Medical Data Annotation jobs in Connecticut?

The most popular types of Medical Data Annotation jobs in Connecticut are:

What are popular job titles related to Internship Medical Data Annotation jobs in Connecticut?

For Internship Medical Data Annotation jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Internship Medical Data Annotation jobs in Connecticut look for?

The top searched job categories for Internship Medical Data Annotation jobs in Connecticut are:

What cities in Connecticut are hiring for Internship Medical Data Annotation jobs?

Cities in Connecticut with the most Internship Medical Data Annotation job openings:

Infographic showing various Internship Medical Data Annotation job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 14% Part Time, 3% Temporary, and 6% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Medical Microbiology Consultant - Remote

micro1 AI

Waterbury, CT • Remote

$70 - $90/hr

Part-time

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


Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.