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$15

$28

$38

How much do biomedical masters jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for biomedical masters 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 jobs can you get with a master's in BME?

A master's in biomedical engineering (BME) can lead to roles such as biomedical engineer, clinical engineer, research scientist, or product development engineer. These positions often require knowledge of medical devices, regulatory standards, and proficiency with tools like CAD software or lab equipment.

Is it worth doing a master's in biomedical science?

A master's in biomedical science can enhance knowledge of human biology, laboratory techniques, and research skills, which are valuable for roles such as biomedical researchers, lab technicians, or clinical trial coordinators. It may improve job prospects and earning potential but requires time and financial investment, so its value depends on career goals and industry demand.

What is the difference between Biomedical Masters vs Biomedical Technician?

CriteriaBiomedical MastersBiomedical Technician
Required CredentialsMaster's degree in biomedical engineering or related fieldAssociate's or bachelor's degree in biomedical technology or related field
Work EnvironmentResearch labs, hospitals, biotech companiesHospitals, clinics, medical equipment companies
Employer & Industry UsageResearch institutions, biotech firms, medical device companiesHealthcare facilities, medical equipment service providers

The Biomedical Masters degree prepares individuals for advanced roles in research, development, and design within the biomedical industry, often involving project management and innovation. In contrast, Biomedical Technicians focus on maintaining, repairing, and installing medical equipment, typically requiring less formal education but strong technical skills. Both roles are essential in healthcare, but they differ in responsibilities, education requirements, and work settings.

What can I do with a master in biomedical science?

A master in biomedical science prepares individuals for roles such as research scientist, laboratory technician, or clinical research coordinator. Graduates can work in healthcare, pharmaceutical companies, biotech firms, or research institutions, often utilizing skills in laboratory techniques, data analysis, and scientific communication.

What are Biomedical Masters?

A Biomedical Masters refers to a graduate-level degree program focused on the study of biological and medical sciences. These programs often combine coursework and research in areas such as molecular biology, physiology, biomedical engineering, and clinical applications. Graduates are prepared for careers in research, healthcare, biotechnology, or may continue on to doctoral or professional medical degrees. A Biomedical Masters can enhance job prospects in hospitals, research institutions, and pharmaceutical companies.

What can I do with a master's in biomedical technology?

A master's in biomedical technology prepares graduates for roles such as biomedical engineer, clinical researcher, or medical device technician. These positions involve designing, testing, and maintaining medical equipment, often requiring knowledge of biology, engineering, and regulatory standards. Job opportunities are available in healthcare facilities, research institutions, and medical device companies.

What types of projects and collaborations can I expect as a Biomedical Masters graduate in a research or industry setting?

As a Biomedical Masters graduate, you can expect to work on multidisciplinary projects that often involve collaboration with professionals in fields such as engineering, biology, medicine, and data science. Your daily responsibilities may include designing experiments, analyzing biological data, and developing biomedical devices or technologies. In both research labs and industry settings, teamwork is essential, and you’ll frequently contribute your expertise to joint efforts aimed at solving complex health-related problems. These collaborations not only expand your technical skills but also offer opportunities to network and advance within your chosen specialization.

What are the key skills and qualifications needed to thrive as a Biomedical Scientist with a master's degree, and why are they important?

To excel as a Biomedical Scientist with a master's degree, you need a solid background in biology, laboratory techniques, data analysis, and scientific research, typically supported by a relevant MSc or MRes. Familiarity with laboratory information management systems (LIMS), advanced microscopy, PCR, and statistical software like SPSS or R is often required. Strong problem-solving skills, attention to detail, and the ability to communicate complex findings clearly help professionals stand out. Mastery of these skills ensures accurate research outcomes, effective collaboration, and ongoing advancement in biomedical science.
More about Biomedical Masters jobs
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What job categories do people searching Biomedical Masters jobs look for? The top searched job categories for Biomedical Masters jobs are:
Biomedical Masters jobs near you
Infographic showing various Biomedical Masters job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 14% Part Time, and 1% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $59,333 per year, or $28.5 per hour.

Data Scientist/AI Lead

Program Management Solutions LLC

Rockville, MD • On-site

Full-time

Posted 5 days ago

Job description

Salary:

Program Management Solutions is looking for a Data Scientist/AI Lead to join our growing team. This is an on-site position that's located in Rockville, MD.
Requirements

  • Bachelors degree in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Bioinformatics, Biomedical Informatics, Computational Biology, Engineering, or related field.
  • Minimum 10+ years of experience supporting data science, artificial intelligence, machine learning, informatics, analytics, data engineering, or scientific computing initiatives.
  • Minimum 5+ years of experience leading technical teams supporting data-intensive, AIenabled, or scientific computing environments.
  • Experience designing and implementing data architectures, ingestion pipelines, metadata management, and data governance frameworks.
  • Experience supporting FAIR data principles, data harmonization, interoperability, and scientific data lifecycle management.
  • Experience developing, integrating, or supporting AI/ML-enabled analytics, predictive modeling, automation, or advanced computational workflows.
  • Experience designing, deploying, or supporting Generative AI (GenAI) solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent assistants, AI agents, prompt engineering, and enterprise knowledge management solutions.
  • Experience supporting responsible AI practices, including model documentation, transparency, explainability, performance monitoring, and bias identification or mitigation.
  • Experience supporting cloud, high-performance computing, GPU-enabled, or large-scale analytics platforms.
  • Experience implementing Machine Learning Operations (MLOps) practices including model lifecycle management, model registries, feature engineering pipelines, automated retraining, version control, deployment automation, and continuous model monitoring.
  • Experience supporting vector databases, semantic search, knowledge graphs, embeddings, enterprise search, and AI-enabled knowledge management platforms.
  • Experience briefing technical and executive stakeholders.


Preferences

  • Masters degree or higher in a related field.
  • Experience supportingNIH, HHS, or biomedical research organizations.
  • Experience with bioinformatics, cheminformatics, knowledge graphs, ontology management, and translational science data environments.
  • Experience supporting AI-enabled analytics, machine learning operations, advanced scientific computing, high-content imaging, or large-scale biomedical data environments.
  • Experience with human-in-the-loop AI workflows, image segmentation, model validation, or AI-enabled scientific platformintegration.
  • Experience supporting enterprise Generative AI platforms using Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenAI APIs, Hugging Face, LangChain, Semantic Kernel, or equivalent technologies.
  • Experience supporting AI governance, AI security, prompt management, model evaluation, AI red teaming, or enterprise AI adoption initiatives.
  • Experience integrating GenAI capabilities into scientific research, biomedical informatics, or decision-support environments.