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How much do remote integrative physiology jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for remote integrative physiology in the United States is $21.50, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $22.84 per hour, depending on experience, location, and employer.

What is the difference between Remote Integrative Physiology vs Remote Exercise Physiologist?

AspectRemote Integrative PhysiologyRemote Exercise Physiologist
Required CredentialsMaster's or PhD in Physiology, certifications like ACSM or NSCABachelor's or Master's in Exercise Science, certifications like ACSM or NSCA
Work EnvironmentResearch, health consulting, wellness programs, often in healthcare or academic settingsPatient assessment, fitness programming, health coaching, often in clinical or fitness settings
Employer & Industry UsageUniversities, research institutes, healthcare companiesHospitals, clinics, fitness centers, telehealth services

Remote Integrative Physiology focuses on understanding complex bodily systems through research and health consulting, often requiring advanced degrees. Remote Exercise Physiologists primarily develop fitness and rehabilitation programs for clients, with a focus on exercise science certifications. Both roles may work remotely but serve different purposes within health and wellness industries.

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Remote Integrative Physiology jobs near you
Infographic showing various Remote Integrative Physiology job openings in the United States as of August 2026, with employment types broken down into 4% As Needed, 63% Full Time, 31% Part Time, and 2% Contract. Highlights an 85% Physical, and 15% Remote job distribution, with an average salary of $44,724 per year, or $21.5 per hour.

Medical Microbiology Consultant - Remote

micro1 AI

Coral Springs, FL • Remote

$70 - $90/hr

Part-time

Posted 17 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.

Apply