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Biomedical Ai Jobs (NOW HIRING)

Spectral MD Inc

Biomedical Engineer

Dallas, TX · On-site

Position Summary: The Biomedical Engineer I will assist in all aspects of design, development ... Spectral AI, Inc. is an equal opportunity and affirmative action employer. All applicants will be ...

Natera

OR

$232K - $243K/yr

... biomedical AI agents, AI-driven analysis platforms, forecasting algorithms. * Identify high-value use cases across drug development (e.g., trial design, patient selection, translational insights ...

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How much do biomedical ai jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for biomedical ai in the United States is $28.53, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $32.21 per hour, depending on experience, location, and employer.

What are some typical challenges faced by professionals working in Biomedical AI, and how can applicants prepare to address them?

Professionals in Biomedical AI often encounter challenges such as integrating diverse data types (e.g., imaging, genomics, clinical records), ensuring data privacy and compliance with healthcare regulations, and translating AI models into clinically actionable insights. To prepare, applicants should familiarize themselves with healthcare data standards, develop strong interdisciplinary communication skills, and stay updated on ethical considerations in medical AI. Experience working with real-world biomedical datasets and collaborating with clinicians or researchers will also be highly valuable.

What are the key skills and qualifications needed to thrive as a Biomedical AI Specialist, and why are they important?

To thrive as a Biomedical AI Specialist, you need a solid background in biomedical sciences, computer science, and machine learning, often supported by an advanced degree (e.g., MS or PhD) in a related field. Familiarity with programming languages like Python or R, experience with AI frameworks (such as TensorFlow or PyTorch), and knowledge of healthcare data systems are essential. Strong analytical thinking, problem-solving abilities, and the capacity to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These competencies enable the effective development and deployment of AI solutions that address critical challenges in biomedical research and healthcare delivery.

What is Biomedical AI?

Biomedical AI refers to the application of artificial intelligence technologies in the field of biomedical research and healthcare. This includes using machine learning, deep learning, and data analytics to analyze complex biological data, improve diagnostics, personalize treatment, and accelerate drug discovery. Biomedical AI professionals work at the intersection of computer science, biology, and medicine, developing tools that can help interpret medical images, predict disease outcomes, and uncover new insights from large-scale health data. The field is rapidly growing and is seen as a key driver in the future of healthcare innovation.

What is the difference between Biomedical Ai vs Biomedical Data Scientist?

AspectBiomedical AiBiomedical Data Scientist
Required CredentialsDegree in AI, Machine Learning, or related fields; knowledge of biology and healthcareDegree in Data Science, Statistics, or related; strong biology background
Work EnvironmentResearch labs, healthcare tech companies, biotech firmsHospitals, research institutions, biotech companies
Employer & Industry UsageDevelops AI models for medical diagnosis, drug discovery, personalized medicineAnalyzes biomedical data to extract insights, support clinical decisions

Biomedical Ai focuses on developing AI algorithms for healthcare applications, combining AI expertise with biomedical knowledge. Biomedical Data Scientists analyze biomedical data to generate insights and support research. While both roles require a strong understanding of biology and data skills, Biomedical Ai emphasizes AI model development, whereas Biomedical Data Scientists focus on data analysis and interpretation.

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Biomedical Ai jobs near you
Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI

Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI

Harvard University

Cambridge, MA • On-site

$75K/yr

Full-time

Posted 18 days ago

Harvard University rating

8.1

Company rating: 8.1 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

131st of 534 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI
School
Harvard T.H. Chan School of Public Health
Department/Area
Biostatistics
Position Description
The Department of Biostatistics at the Harvard T.H. Chan School of Public Health invites applications for a Postdoctoral Research Fellow position in statistics, genetics, and biomedical AI. The lab develops cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and computational challenges arising in precision medicine, mental health, and biomedical informatics.
The postdoctoral fellow will contribute to projects focused on:
  • Foundation and representation learning for multimodal biomedical data, including electronic health records (EHRs), genomics, imaging, and clinical text to power next-generation precision medicine.
  • Statistical and computational genomics across diverse populations and biobanks for risk prediction, genetic discovery, and genomic medicine.
  • Federated and transfer learning for distributed and privacy-preserving data integration.
  • AI and Deep learning approaches to high-dimensional and multi-modal biomedical data.
  • Causal Inference, Fairness, and Trustworthy AI in real-world healthcare applications.

Our group actively collaborates with large national and international initiatives, including Mass General Brigham, Penn Medicine, Cambridge Health Alliance, PsycheMERGE Network, PCORnet, and OHDSI, providing unique opportunities to work with massive EHR-genomic datasets and multi-site real-world evidence networks.
Basic Qualifications
  • Ph.D. in Statistics, Biostatistics, Computer Science, Statistical Genetics, or a related quantitative field (by the time of appointment).
  • Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis.
  • Proficiency in R or Python; experience with deep learning, causal inference, or genetic data analysis is not required but encouraged.
  • Excellent written and verbal communication skills.

Additional Qualifications
Special Instructions
The position is available immediately. The initial appointment is for one year, renewable based on performance and funding. Salary and benefits follow NIH and Harvard guidelines.
Interested applicants should submit a CV, cover letter, and contact information for three references to Dr. Rui Duan (rduan@hsph.harvard.edu). Review of applications will begin immediately and continue until the position is filled.
Contact Information
Rui Duan, Associate Professor, Department of Biostatistics
Contact Email
rduan@hsph.harvard.edu
Salary Range
$75,000
Minimum Number of References Required
3
Maximum Number of References Allowed
Keywords
biostatistics; AI; biomedical informatics; statistics; genetics

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