Data Science & AI Intern

University of Miami•Miami, FL

1d•Onsite

About The Position

The Sylvester Data Science and AI Innovations Internship Program provides supervised training for students, trainees, research fellows, and others interested in developing tools to analyze and visualize oncology clinical and research data. The intern processes and analyzes molecular, sociodemographic, psychosocial, patient-reported, lifestyle, wearable, and other clinical and research data, along with publicly available population- and neighborhood-level datasets. Activities take place across Sylvester research laboratories and the Sylvester Survivorship and Supportive Care Institute. This is a casual-worker role providing services on an irregular or flexible basis to meet fluctuating University demand and assist departments with deadlines and institutional objectives.

Requirements

High school diploma or equivalent/relevant experience, certification, or license.
At least 1 year of relevant experience.
Ability to learn procedures, technologies, and protocols and adapt to changing priorities and work demands.
Ability to collaborate and contribute to a team environment.
Proficiency with office software, technology, and relevant computer applications.
Strong written and verbal communication skills.
Interest in using AI and computational and data-visualization approaches in oncology, clinical research, precision medicine, cancer survivorship, digital health, lifestyle medicine, or biomedical data sciences.

Nice To Haves

Experience or coursework in Python, R, SQL, JavaScript, statistics, data visualization, software development, or related tools.
Strong organization, communication, and team science skills.
Experience with Git, reproducible workflows, software testing, or application development.
Familiarity with cloud-based development environments such as Azure.
Familiarity with developing, training, and evaluating AI models.

Responsibilities

Perform assigned tasks and projects.
Provide clerical, research, professional, or technical support to the assigned division.
Follow company, University, and unit-level policies and procedures, and safeguard University assets.
Meet or exceed applicable goals and deadlines.
Develop relationships with department staff and other parties to carry out job functions.
Keep supervising staff informed of work progress and issues encountered.
Develop foundational knowledge of oncology research, including sociodemographic, psychosocial, biobehavioral, lifestyle, wearable, patient-reported outcomes, intervention mechanisms, molecular, and digital health data.
Support supervised cleaning, documentation, harmonization, and integration of diverse clinical and research datasets.
Assist with analysis and technical work linking individual-level clinical, genomics, digital health, and patient-reported outcomes data with sociodemographic, neighborhood, and population-level data.
Contribute to research on how clinical, behavioral, social, and population-level factors guide cancer care and influence outcomes across cancer sites and treatment modalities.
Support development and evaluation of AI-driven risk algorithms, analytic tools, dashboards, and AI-enabled applications for visualizing, interpreting, and using clinical and research data.
Support development and evaluation of digital health, precision medicine, and supportive care tools and software.
Assist in developing and implementing risk-tailored, AI-powered adjunctive supportive care interventions delivered through eHealth platforms.
Participate in regular individual and small-group meetings with mentors and program faculty to review data pipelines, troubleshoot methods, refine research questions, and clarify role expectations.