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Data Annotation Biology Jobs in Indiana (NOW HIRING)

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Data Annotation Biology information

What is the difference between Data Annotation Biology vs Data Labeling Specialist?

AspectData Annotation BiologyData Labeling Specialist
Required CredentialsBiology degree or related certificationHigh school diploma or equivalent, training in labeling tools
Work EnvironmentLaboratory, research settings, or remoteOffice, remote, or data centers
Industry UsageBiotech, healthcare, researchTech, AI, machine learning
Job FocusAnnotating biological data, images, and sequencesLabeling various data types for AI models

Data Annotation Biology involves annotating biological data, often requiring a background in biology, while Data Labeling Specialists focus on labeling diverse data types for AI applications, with less emphasis on biological expertise. Both roles are essential in data preparation but serve different industry needs.

What is data annotation in biology?

Data annotation in biology involves labeling or tagging biological data—such as images, gene sequences, or medical records—with relevant information to make it useful for research and machine learning. Annotators may identify specific features, mark regions of interest, or classify data according to biological characteristics. This work is crucial for training artificial intelligence systems to recognize patterns, make predictions, and automate analyses in biological research. Annotated datasets help improve the accuracy and reliability of computational models in genomics, microscopy, drug discovery, and more.

What are the key skills and qualifications needed to thrive as a data annotation biology specialist, and why are they important?

To thrive as a Data Annotation Biology specialist, you need a solid background in biological sciences, attention to detail, and experience handling scientific datasets, often supported by a degree in biology or a related field. Familiarity with annotation tools, bioinformatics databases, and software such as BLAST or Ensembl is typically required, alongside knowledge of data management systems. Strong analytical thinking, precision, and good communication skills help you interpret complex biological data and collaborate effectively with researchers. These skills ensure the accuracy and utility of annotated datasets, which are critical for advancing biological research and data-driven discoveries.

What are the unique challenges faced by data annotators working with biological datasets, and how can they be addressed?

Data annotators in biology often encounter challenges such as dealing with complex, high-dimensional data (like gene sequences or microscopy images) and the need for a deep understanding of biological terminology and context. Errors in annotation can significantly impact downstream research or machine learning models, so maintaining accuracy is crucial. Collaborating closely with biologists and domain experts helps ensure consistency and correctness, while ongoing training and clear annotation guidelines help address ambiguities. Staying up-to-date with evolving biological standards and tools is also essential for success in this role.
What are popular job titles related to Data Annotation Biology jobs in Indiana? For Data Annotation Biology jobs in Indiana, the most frequently searched job titles are:
Infographic showing various Data Annotation Biology job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 49% Full Time, 46% Part Time, 3% Contract, and 1% Nights. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.

AI Trainer - Microbiology Expert

micro1 AI

Carmel, IN • Remote

$70 - $90/hr

Part-time

Posted 7 days ago


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.