Digbi Health · 3 hours ago

Computer Science Intern

United States

Internship

Remote

Intern/New Grad

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Responsibilities

AI Model Development: Collaborate with the AI/ML team to design, implement, and optimize machine learning models for predicting and analyzing biological data, such as genomic sequences, microbiome data, and metabolic profiles.

Data Integration: Assist in integrating diverse biological data sources (genomics, microbiomics, clinical, etc.) to create unified data pipelines for AI model training and analysis.

Software Development: Contribute to the development and optimization of algorithms and software tools that process large biological datasets and generate actionable insights.

Data Analysis: Perform exploratory data analysis to identify patterns and trends in biological data, and work with scientists to interpret the findings.

Collaboration: Work closely with cross-functional teams, including bioinformaticians, data scientists, and software engineers, to drive projects from concept to deployment.

Research & Development: Participate in ongoing research to stay up to date with the latest trends in AI, machine learning, and precision biology.

Qualification

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PythonAI/ML frameworksJavaReactCloud computingAWSGoogle CloudGitBiology understandingGenomics understandingHealthcare data understandingData analysis

Required

Currently pursuing a degree in Computer Science(Bachelor’s or Master’s level).

Strong proficiency in programming languages such as Python, Java, or React.

Experience with AI/ML frameworks and libraries.

Strong problem-solving skills and the ability to analyze and interpret complex datasets.

Excellent written and verbal communication skills to present technical concepts to both technical and non-technical team members.

Ability to collaborate in a fast-paced, dynamic environment and work effectively within interdisciplinary teams.

Preferred

Experience with cloud computing platforms (e.g., AWS, Google Cloud) and version control (e.g., Git) is desirable.

A basic understanding of biology, genomics, and healthcare data is desirable but not required. Willingness to learn about precision biology is essential.