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Ai Medical Researcher information

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$30K

$113.1K

$164.5K

How much do ai medical researcher jobs pay per year?

As of Jul 16, 2026, the average yearly pay for ai medical researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is the difference between Ai Medical Researcher vs Data Scientist in Healthcare?

AspectAi Medical ResearcherData Scientist in Healthcare
Required CredentialsAdvanced degrees in AI, machine learning, or biomedical fields; certifications in AI toolsDegree in data science, statistics, or related fields; certifications in data analysis and programming
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHospitals, healthcare tech firms, research organizations
Employer & Industry UsageMedical research, biotech, AI-focused healthcare startupsHealthcare providers, pharmaceutical companies, health tech firms

While both roles involve data analysis and AI, Ai Medical Researchers focus specifically on developing AI models for medical applications, whereas Data Scientists in Healthcare analyze healthcare data to inform decisions. The roles often overlap but differ mainly in their focus on AI development versus data analysis.

What does an AI Medical Researcher do?

An AI Medical Researcher applies artificial intelligence, machine learning, and data analysis techniques to medical and healthcare problems. They develop algorithms to analyze medical data, such as patient records or imaging, to assist in diagnosis, treatment planning, and drug discovery. Their work often involves collaborating with clinicians, data scientists, and other researchers to create innovative solutions that improve patient outcomes and advance medical knowledge.

What are some typical challenges faced by AI Medical Researchers when collaborating with healthcare professionals?

AI Medical Researchers often encounter challenges such as bridging the communication gap between technical teams and healthcare professionals, as medical practitioners may not always be familiar with AI concepts and terminology. Additionally, integrating AI solutions into existing clinical workflows can be complex due to regulatory requirements, data privacy concerns, and the need for high-quality annotated medical data. Successful collaboration requires a proactive approach to interdisciplinary teamwork, frequent knowledge sharing, and a strong focus on practical, patient-centered outcomes.

What are the key skills and qualifications needed to thrive as an AI Medical Researcher, and why are they important?

To thrive as an AI Medical Researcher, you need a strong background in computer science, biomedical sciences, and statistics, often supported by a PhD or relevant advanced degree. Proficiency in programming languages (such as Python or R), machine learning frameworks, and experience with medical data analysis tools are typically required. Critical thinking, interdisciplinary collaboration, and effective communication help researchers bridge the gap between technical innovation and clinical application. These skills are essential to develop impactful AI solutions that advance medical research and improve patient outcomes.
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Ai Medical Researcher jobs near you
Physics Researcher - Fully Remote | Upto $140/hr

Physics Researcher - Fully Remote | Upto $140/hr

Mercor

New York, NY • Remote

$140/hr

Full-time

Re-posted 13 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Research Physics Expert
Type: Contract
Compensation: $80–$140/hour
Location: Remote
Commitment: ~10 hours/week

Role Responsibilities

  • Solve research-level physics challenges end-to-end with verifiable derivations, code, and peer-reviewed references.
  • Decompose challenges into standalone checkpoint sub-problems requiring genuine physical reasoning.
  • Author Python answer templates with auto-grading functions for symbolic or numerical answers.
  • Audit submitted solutions for correctness, scope, and method soundness; deliver actionable feedback across iterations.
  • Adjudicate between parallel solver attempts and decide which solution becomes the golden reference.
  • Document chain-of-thought reasoning, error tolerances, equivalent symbolic forms, and verification test cases.

Qualifications

Must-Have

  • PhD or postdoc in the relevant subfield (senior PhD student minimum).
  • Postdoc or junior professor in the relevant subfield (PhD minimum).
  • Full professor or industry research PI in the relevant subfield (senior postdoc or junior professor minimum).
  • Hands-on familiarity with at least two canonical methods of the target subfield, demonstrable through publications.
  • 3–5 representative publications (arXiv ID or DOI), ideally within the last ~5 years and in the target subfield.
  • Working proficiency with LaTeX, Python, Jupyter, and SymPy.
  • Strong written English (B2/C1/C2 minimum; native or near-native preferred).

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.