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Ai Biomedical Internship Jobs (NOW HIRING)

... interns toward achieving lab and project goals. * Funding Opportunities: Identifying and ... application across biomedical and chemical sciences. * Molecular and Structural AI: Hands-on ...

This internship is designed for students who want handson experience building reliable, performant ... Please contact AI.Questions@lrs.com with any questions.

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How much do ai biomedical internship jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for ai biomedical internship in the United States is $15.16, according to ZipRecruiter salary data. Most workers in this role earn between $9.62 and $17.55 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during an AI biomedical internship?

As an AI Biomedical Intern, you will likely engage in projects that combine data analysis, machine learning, and biomedical research. Typical tasks may include cleaning and preprocessing biomedical data, developing predictive models for clinical outcomes, and collaborating with researchers or clinicians to interpret results. You may also participate in literature reviews, contribute to writing research reports, and attend regular team meetings. This hands-on experience is designed to help you build both your technical and domain-specific skills, and you'll often work closely with mentors from both data science and biomedical backgrounds.

What is an AI biomedical internship?

An AI Biomedical Internship is a temporary position, typically for students or recent graduates, where individuals gain hands-on experience applying artificial intelligence techniques to solve problems in biomedical research and healthcare. Interns may work on projects involving medical imaging, data analysis, drug discovery, or healthcare diagnostics, often using machine learning and deep learning tools. These internships provide valuable exposure to real-world biomedical datasets, multidisciplinary teamwork, and the latest AI technologies, preparing interns for careers at the intersection of technology and medicine.

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

To thrive as an AI Biomedical Intern, you need a strong background in biomedical sciences, data analysis, and machine learning concepts, often supported by coursework or a degree in related fields. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of AI frameworks such as TensorFlow or PyTorch are typically required. Strong problem-solving abilities, teamwork, and effective communication skills help interns contribute meaningfully to research projects and collaborate with multidisciplinary teams. These skills are crucial for successfully integrating AI solutions into biomedical challenges and advancing research outcomes.
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Infographic showing various Ai Biomedical Internship job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $31,529 per year, or $15.2 per hour.

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Job description

Position Summary

The University of Alabama at Birmingham invites qualified candidates to apply for a Scientist III position in the Systems Pharmacology AI Research Center (SPARC) department. The candidate will frequently encounter high-level complexities that demand sharp judgment and rigorous decision-making. The role requires deep technical expertise across AI for science protein and antibody design, AI-driven molecular dynamics, agentic AI and autonomous research systems, clinical trial simulations, virtual cell modeling, multi-modal drug discovery, and retrosynthesis; combined with a strategic orientation toward research planning, execution, and translation. The selected candidate will lead the development of novel AI models and software systems that form essential components of SPARC's AI-accelerated drug discovery pipeline, direct in silico computational studies, and lead lab-in-the-loop collaborations with UAB, regional, and national experimental partners. Obtaining AI drug discovery research funding as a Co-Principal Investigator or Co-Investigator on extramural grant proposals is a major and recurring responsibility, alongside leading SPARC service activities not covered by existing external funding and authoring scientific manuscripts, progress reports, and grant documentation. Active research areas include protein and antibody design, novel AI approaches to molecular dynamics simulations, agentic AI and autonomous systems for science, clinical trial simulations, virtual cell modeling, multi-modal drug discovery, retrosynthesis, and AI for science more broadly. Excellent office, programming, and communication skills are essential. SPARC offers GPU/HPC infrastructure, large biomedical data assets, deep clinical partnerships, and direct opportunities to translate methodological advances into impact across the UAB School of Medicine.

General Responsibilities

  • To interpret, organize, execute and coordinate research assignments.

  • To formulate and conduct research on problems of considerable scope and complexity.

  • To explore subject area and define scope and selection of problems for investigation through conceptually related studies or series of projects of lesser scope.

Key Duties & Responsibilities

  1. Research Direction: Deciding the focus of the lab's research agenda, including selection of research projects that align with both current scientific needs and future potential.

  2. Methodological Choices: Making choices about research methodologies, including the selection of appropriate AI algorithms, data sources, and experimental designs that maximize the potential for impactful findings.

  3. Resource Allocation: Determining how to allocate limited resources, such as lab equipment, funding, and personnel time, in a manner that optimally supports ongoing and future research efforts.

  4. Team Leadership: Making decisions about the mentoring and development of research staff, prioritizing areas for skills development and guiding research assistants and interns toward achieving lab and project goals.

  5. Funding Opportunities: Identifying and prioritizing grant and external funding opportunities that will offer the highest yield for the lab's objectives, including making decisions on when and how to pursue these opportunities.

  6. Commercial Partnerships: Judging the viability and potential of industrial and commercial collaborations and deciding the terms under which these collaborations will proceed to ensure the mutual benefit of all stakeholders.

  7. Publication and Dissemination: Deciding when research findings are robust and significant enough for publication and choosing the appropriate platforms and journals for dissemination to ensure maximum impact.

  8. Perform other duties as assigned.

Salary Range:   $ 80,300- $ 133,300

Qualifications

Doctor of Philosophy, D.V.M. or M.D. degree in a related field and six (6) years of related experience OR M.D. and Master's degree and four (4) years of related experience required. Work experience may NOT substitute for education requirement.

Preferences

  • Doctor of Philosophy (PhD) in biomedical informatics, computing, computer science, data science, artificial intelligence, or a closely related field. PhD completed within the last 10 years preferred.

  • AI/ML Expertise: Deep proficiency with modern machine learning, including deep learning, transformers, graph neural networks, generative models, and foundation models and their application across biomedical and chemical sciences. 

  • Molecular and Structural AI: Hands-on experience with novel AI approaches to molecular dynamics simulations, protein/antibody structure prediction and design, retrosynthesis, and multi-modal drug discovery. 

  • Programming and Engineering: Strong Python skills (PyTorch / JAX / TensorFlow); comfortable with HPC and GPU workflows, modern MLOps, and reproducible computational pipelines.

  • Agentic and Autonomous AI: Experience designing agentic AI workflows or autonomous research systems for science, including LLM tool-use, retrieval-augmented pipelines, and self-driving experimentation loops.   

  • Statistical and Causal Reasoning: Strong statistical foundations including hypothesis testing, Bayesian inference, uncertainty quantification, and causal modeling for biomedical data.  

  • Biomedical Data at Scale: Familiarity with large-scale biomedical, omics, imaging, clinical-trial, and chemical datasets, including data integration across modalities for virtual-cell and multi-modal drug-discovery applications.

Key Skills

  • Leadership: Ability to lead, guide, and mentor a team of researchers and students. 

  • Communication: Excellent verbal and written communication skills for publishing research, delivering presentations, and grant writing. 

  • Collaboration: Ability to work efficiently in a multidisciplinary environment, with the capability to integrate various scientific domains. 

  • Problem-Solving: Strong analytical thinking and the ability to approach complex scientific problems creatively. 

  • Time Management: Ability to manage multiple projects and deadlines effectively.


 

UAB is an Equal Employment/Equal Educational Opportunity Institution dedicated to providing equal opportunities and equal access to all individuals regardless of race, color, religion, ethnic or national origin, sex (including pregnancy), genetic information, age, disability, and veteran's status. As required by Title IX, UAB prohibits sex discrimination in any education program or activity that it operates. Individuals may report concerns or questions to UAB's Assistant Vice President and Senior Title IX Coordinator. The Title IX notice of nondiscrimination is located at uab.edu/titleix.


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