Job Description Summary

We're looking for undergraduate science major students, preferably from biology, statistics, or computer science, with strong statistical and computational skills who are passionate about applying data science and quantitative methods to advance medicine and healthcare. You will work with leading researchers and domain experts to analyze complex biological and clinical datasets, contribute to cutting-edge research, and support the development of next-generation data-driven solutions in healthcare. Our research agenda includes, but is not limited to: • Analysis of large-scale biological and clinical datasets (e.g., genomics, medical imaging, electronic health records) • Application of statistical modeling and machine learning to understand disease mechanisms and progression • Integration of multimodal data for improved diagnosis, patient stratification, and outcome prediction • Data-driven approaches to support clinical decision-making and healthcare efficiency • Reproducible and responsible data science (e.g., interpretability, robustness, and bias awareness)

Job Description

Key Responsibilities:

Analyze large-scale biological and healthcare datasets using statistical and computational methods
Apply statistical modeling techniques and, where appropriate, machine learning approaches to support research questions
Contribute to the design and development of machine learning models (including exposure to deep learning and LLM-based approaches) to support automation of clinical or research tasks using data such as medical images, electronic health records, waveforms, and clinical reports
Write and maintain code in R and/or Python for data cleaning, transformation, analysis, and visualization
Perform statistical validation, error estimation, and interpretation of model and analysis results across diverse datasets
Assist in building prototypes and reproducible workflows that support scalable, high-quality research and algorithm development
Collaborate with researchers to translate biological and clinical questions into quantitative analyses and data-driven solutions
Support the exploration and evaluation of new methodologies, tools, and technologies in data science, machine learning, and healthcare applications
Contribute to preparation of research outputs, including visualizations, reports, and potential publications

Basic Qualifications:

Currently enrolled in a Bachelor’s degree in Biology, Biostatistics, Bioinformatics, or a related field
Strong foundation in statistics (e.g., hypothesis testing, regression, data analysis)
Proficiency in R and/or Python for data analysis
Familiarity with at least one area of machine learning concepts such as Computer Vision, Deep Learning, or Algorithmic Foundations of Optimization
Experience working with large datasets and data wrangling techniques
Ability to interpret and communicate quantitative results in a biological or clinical context
Strong problem-solving skills and ability to work under research supervision

Preferred Qualifications:

Exposure to machine learning or AI concepts (e.g., classification, clustering, predictive modeling)
Familiarity with biological or clinical data types (e.g., genomics, imaging, EHR data)
Experience with data visualization tools (e.g., ggplot2, matplotlib, seaborn)
Knowledge of reproducible research practices (e.g., version control, scripting workflows)
Interest in contributing to research publications or presentations.

At GE HealthCare, we are committed to bringing AI and cloud-based solutions for our customers: all aspects of intelligent computing services across the cloud and. Sitting within the centralized Science & Technology organization, our AI org is harnessing the power of AI to make healthcare more precise, more personalized, and more accessible for everyone. From driving the overall clinical research and patient-centric innovation strategy to delivering new digital and machine learning capabilities - we’re committed to leading digital transformation, improving outcomes for patients and providers, and creating a world where healthcare has no limits.

As an AI research intern at GEHC, you get to work on the most cutting-edge and exciting projects. You will have access to petabytes of data, state of the art computing resources, and professional support from domain experts.

The pay rate for this position is $45-57hr.

We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Additional Information

GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).

While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.

**Relocation Assistance Provided: **No

Job Description Summary

Job Description

Key Responsibilities:

Analyze large-scale biological and healthcare datasets using statistical and computational methods

Apply statistical modeling techniques and, where appropriate, machine learning approaches to support research questions

Contribute to the design and development of machine learning models (including exposure to deep learning and LLM-based approaches) to support automation of clinical or research tasks using data such as medical images, electronic health records, waveforms, and clinical reports

Write and maintain code in R and/or Python for data cleaning, transformation, analysis, and visualization

Perform statistical validation, error estimation, and interpretation of model and analysis results across diverse datasets

Assist in building prototypes and reproducible workflows that support scalable, high-quality research and algorithm development

Collaborate with researchers to translate biological and clinical questions into quantitative analyses and data-driven solutions

Support the exploration and evaluation of new methodologies, tools, and technologies in data science, machine learning, and healthcare applications

Contribute to preparation of research outputs, including visualizations, reports, and potential publications

Basic Qualifications:

Currently enrolled in a Bachelor’s degree in Biology, Biostatistics, Bioinformatics, or a related field

Strong foundation in statistics (e.g., hypothesis testing, regression, data analysis)

Proficiency in R and/or Python for data analysis

Familiarity with at least one area of machine learning concepts such as Computer Vision, Deep Learning, or Algorithmic Foundations of Optimization

Experience working with large datasets and data wrangling techniques

Ability to interpret and communicate quantitative results in a biological or clinical context

Strong problem-solving skills and ability to work under research supervision

Preferred Qualifications:

Exposure to machine learning or AI concepts (e.g., classification, clustering, predictive modeling)

Familiarity with biological or clinical data types (e.g., genomics, imaging, EHR data)

Experience with data visualization tools (e.g., ggplot2, matplotlib, seaborn)

Knowledge of reproducible research practices (e.g., version control, scripting workflows)

Interest in contributing to research publications or presentations.

The pay rate for this position is $45-57hr.

We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Additional Information

**Relocation Assistance Provided: **No