Data Science & AI Intern

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The University of Miami/UHealth Department of SCCC has an exciting opportunity for a Full-Time Data Science & AI Intern to work at UHealth in Miami, Florida.

CORE JOB SUMMARY

The Sylvester Data Science and AI Innovations Internship Program provides supervised training opportunities for students, trainees, research fellows, and others interested in developing tools to analyze and visualize clinical and research data in oncology. Daily activities will include processing and analyzing molecular, sociodemographic, psychosocial, patient‑reported, lifestyle, wearable, and other clinical and research data, as well as publicly available population‑ and neighborhood‑level datasets. These activities occur across Sylvester’s research laboratories and the Sylvester Survivorship and Supportive Care Institute.

As a Casual Worker, this individual supplies services on an irregular or flexible basis to meet the University’s fluctuating demand for work. Additionally, the Casual Worker assists the assigned department(s) in meeting strict deadlines to advance the institution’s related goals and objectives.

CORE JOB FUNCTIONS

• Performs assigned tasks and projects.
• Provides clerical, research, professional or technical support to assigned division.
• Adheres to all company policies and procedures.
• Meets or exceeds applicable goals and deadlines.
• Develops relationships with department staff and other parties to carry out job functions.
• Keeps supervising staff members informed of work progress and any issues encountered.
• Adheres to University and unit-level policies and procedures and safeguards University assets. This list of duties and responsibilities is not intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary.

DEPARTMENT SPECIFIC:

• Develop foundational knowledge of oncology research with emphasis on sociodemographic, psychosocial, biobehavioral, lifestyle, wearable, patient-reported outcomes, psychosocial and behavioral intervention mechanisms, molecular (e.g., genomic), and digital health data.

• Support supervised data cleaning, documentation, harmonization, and integration of diverse clinical and research datasets.

• Assist with analytic and technical activities that link individual-level clinical, genomics, digital health, and patient-reported outcomes data with sociodemographic, neighborhood, and population-level data.

• Contribute to research examining how clinical, behavioral, social, and population-level factors guide cancer care delivery and influence outcomes across cancer sites and treatment modalities.

• Support the development and evaluation of AI-driven risk algorithms, analytic tools, dashboards, and AI-enabled applications that enhance visualization, interpretation, and use of clinical and research data.

• Support the development and evaluation of digital health, precision medicine, and other 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 one-on-one and small-group meetings with mentors and program faculty to review data pipelines, troubleshoot methods, refine research questions, and clarify role expectations.

CORE QUALIFICATIONS

Education: High School Diploma or equivalent/relevant experience, certification or license

Experience: Minimum 1 year of relevant experience required

Certification and Licensing: Refer to department description for applicable certification requirements

Knowledge, Skills and Abilities:

• Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing priorities and work demands.
• Teamwork: Ability to work collaboratively with others and contribute to a team environment.
• Technical Proficiency: Skilled in using office software, technology, and relevant computer applications.
• Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders.
• Interest in leveraging AI and other computational and data visualization approaches in oncology, clinical research, precision medicine, cancer survivorship, digital health, lifestyle medicine, and biomedical data sciences.

• 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 in developing, training, and evaluating AI models

This is a core job profile description and is not reflective of all duties that may be assigned to a specific position in each individual department. The above statements are intended to describe the general nature and primary responsibilities of this core job profile. Specific duties and tasks may vary based upon departmental needs. Other duties may be assigned to the above consistent with the knowledge, skills, and abilities required for the job.

The University of Miami offers competitive salaries and a comprehensive benefits package including medical, dental, tuition remission and more.

UHealth-University of Miami Health System, South Florida's only university-based health system, provides leading-edge patient care powered by the ground breaking research and medical education at the Miller School of Medicine. As an academic medical center, we are proud to serve South Florida, Latin America and the Caribbean. Our physicians represent more than 100 specialties and sub-specialties, and have more than one million patient encounters each year. Our tradition of excellence has earned worldwide recognition for outstanding teaching, research and patient care. We're the challenge you've been looking for.

The University of Miami is an Equal Opportunity Employer. Applicants and employees are protected from discrimination based on certain categories protected by Federal law.

Job Status:

Full time

Employee Type:

Temporary-Intermittent