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Machine Learning Biomedical Internship Jobs in Columbus, IN

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Machine Learning Biomedical Internship information

See Columbus, IN salary details

$23.7K

$39.6K

$81.8K

How much do machine learning biomedical internship jobs pay per year?

As of Aug 28, 2026, the average yearly pay for machine learning biomedical internship in Columbus, IN is $39,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,200.00 and $42,800.00 per year, depending on experience, location, and employer.

What is a machine learning biomedical internship?

A Machine Learning Biomedical Internship is a temporary position where students or recent graduates work with professionals to apply machine learning techniques in the biomedical field. Interns typically assist with data analysis, model development, and research projects that involve biological or medical data. The goal is to gain practical experience in using artificial intelligence to solve healthcare challenges, such as disease prediction, medical imaging, or drug discovery. These internships often require knowledge of programming languages like Python and familiarity with machine learning frameworks. They provide valuable hands-on experience and networking opportunities for those interested in biomedical data science careers.

What types of projects do interns typically work on during a machine learning biomedical internship?

Interns in Machine Learning Biomedical roles often contribute to projects involving the development and validation of algorithms for analyzing medical data, such as imaging, genomics, or electronic health records. They may assist with data preprocessing, model training, and performance evaluation under the guidance of experienced researchers or engineers. Collaboration is common, as interns often work closely with interdisciplinary teams including data scientists, clinicians, and software engineers. This hands-on experience provides valuable exposure to real-world biomedical challenges while strengthening both technical and communication skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical intern, and why are they important?

To excel as a Machine Learning Biomedical Intern, you need a solid background in computer science, statistics, and biology, often supported by coursework or a degree in related fields. Familiarity with programming languages like Python or R, experience with machine learning libraries (such as TensorFlow or scikit-learn), and knowledge of data analysis tools are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts clearly are crucial soft skills. These competencies enable interns to develop effective models, collaborate with multidisciplinary teams, and contribute meaningful insights to biomedical research projects.

What job categories do people searching Machine Learning Biomedical Internship jobs in Columbus, IN look for?

The top searched job categories for Machine Learning Biomedical Internship jobs in Columbus, IN are:

What cities near Columbus, IN are hiring for Machine Learning Biomedical Internship jobs?

Cities near Columbus, IN with the most Machine Learning Biomedical Internship job openings:

Machine Learning Biomedical Internship jobs near you

Postdoctoral Fellow in Biostatistics & Health Data Science

Bloomington, IN • On-site

Indiana University School of Education
See more jobs at Indiana University School of Educationexternal

$42K - $58K/yr

Full-time

Re-posted 17 days ago

Job description

Job Summary:
The Kinsey Institute is seeking a Postdoctoral Fellow in Biostatistics & Health Data Science to address critical challenges in clinical data harmonization using advanced methodologies. The role involves designing LLM-based methods, collaborating on data integration initiatives, and contributing to grant development within a collaborative environment focused on health equity and real-world data applications.
Responsibilities:
• Design and implement LLM-based methods for clinical data harmonization, semantic normalization, and ontology alignment
• Develop multi-agent or RAG-style (retrieval-augmented generation) workflows for schema matching and terminology mapping
• Collaborate with national and multi-institutional initiatives in data integration and standardization
• Support open-source tooling, reproducible pipelines, and standards-based approaches (e.g., OMOP, FHIR, UMLS)
• Lead or support manuscript preparation and dissemination at top informatics and AI venues
• Contribute to grant development and proposal writing
Qualifications:
Required:
• Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
• Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
• Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
• Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
• Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.
Preferred:
• Experience with concept normalization, ontology mapping, or schema alignment.
• Familiarity with LLM agents, tool-augmented reasoning, or hybrid rules + LLM systems.
• Record of publications in relevant domains (informatics, machine learning, AI, knowledge representation).
• Experience with multi-site data harmonization or federated data environments.
Company:
The Indiana University School of Education is known for preparing reflective, caring, and skilled educators who make a difference in the lives of their students in Indiana, throughout the United States, and around the world. Founded in 1908, the company is headquartered in Bloomington, Indiana, US, , with a team of 201-500 employees. The company is currently Growth Stage.

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