Organization
Centers for Disease Control and Prevention (CDC)
Reference Code
CDC-2026-0092
How To Apply
To submit your application, scroll to the bottom of this opportunity and click APPLY.
A Complete Application Consists Of
- An application
- Transcripts – Click here for detailed information about acceptable transcripts
- A current resume/CV, including academic history, employment history, relevant experiences, and publication list
- One educational or professional recommendation. Your application will be considered incomplete, and will not be reviewed until one recommendation is submitted.
All documents must be in English or include an official English translation.
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Application Deadline
11/6/2026 3:00:00 PM Eastern Time Zone
Description
- Applications will be reviewed on a rolling-basis.
CDC Office and Location: A fellowship opportunity is available at the Public Health Informatics and Analytics Team (PHIAT) in the Office of the Director at the National Center for Environmental Health/Agency for Toxic Substances and Disease Registry (NCEH/ATSDR), Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia.
The Centers for Disease Control and Prevention (CDC) is one of the major operation components of the Department of Health and Human Services. CDC protects America from health, safety and security threats, both foreign and in the U.S. Whether diseases start at home or abroad, are chronic or acute, curable or preventable, human error or deliberate attack, CDC fights disease and supports communities and citizens to do the same. CDC increases the health security of our nation. As the nation’s health protection agency, CDC saves lives and protects people from health threats. To accomplish its mission, CDC conducts important science and provides health information that protects our nation against expensive and dangerous health threats, and responds when these arise.
Research Project: You will have the opportunity to train alongside PHIAT members who are actively involved in various tasks related to data science, data engineering, data analytics, artificial intelligence, machine learning, deep learning, natural language processing, and automation using modern tools and techniques. During this fellowship, you will gain valuable knowledge and skills in training machine learning models and applying Natural Language Processing (NLP) techniques such as Topic Modeling and Named Entity Recognition. Additionally, you will learn how to leverage Large Language Models (LLMs) to address real-world environmental health challenges. You will be immersed in a collaborative multi-disciplinary team environment, participating in both group projects and independent assignments. You will also have the chance to train on routine tasks as well as Proof of Concept (POC) projects, allowing you to apply their newly acquired skills in practical scenarios.
Learning Objectives: Under the guidance of a mentor you will:
- Train alongside PHIAT members on data science, data engineering, analytics, artificial intelligence, machine learning, and automation projects.
- Develop practical experience training and evaluating machine-learning and deep-learning models using modern tools and techniques.
- Build natural language processing skills, including topic modeling, named entity recognition, and text-data analysis.
- Learn to apply large language models to real-world environmental health questions and public health challenges.
- Participate in routine operational activities and proof-of-concept projects that translate technical skills into practical solutions.
- Collaborate in a multidisciplinary team environment while training with both group-based projects and independent assignments.
- Strengthen skills in data preparation, model development, analysis, communication, and the responsible application of AI technologies.
Mentor(s): The mentor for this opportunity is Mohammed Lamtahri ([email protected]). If you have questions about the nature of the research, please contact the mentor(s).
Anticipated Appointment Start Date: 2026. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of CDC and is contingent on the availability of funds.
Level of Participation: The appointment is full time.
Participant Stipend: Stipend rates may vary based on numerous factors, including opportunity, location, education, and experience. If you are interviewed, you can inquire about the exact stipend rate at that time and if selected, your appointment offer will include the monthly stipend rate.
Citizenship Requirements: This opportunity is available to U.S. citizens only.
ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and CDC. Participants do not become employees of CDC, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.
The successful applicant(s) will be required to comply with Environmental, Safety and Health (ES&H) requirements of the hosting facility.
Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email [email protected] and include the reference code for this opportunity.
Qualifications
The qualified candidate should be currently pursuing or have received a bachelor's or master's degree in the one of the relevant fields.
Preferred Skills
- Programming in Python, R, or other common program languages.
- Experience with data wrangling techniques
- Experience with working in a cloud environment (e.g., Microsoft Azure)
- Experience with relational database and general data management
Point of Contact
Rachel
Eligibility Requirements">9 )
- Citizenship: U.S. Citizen Only
- Degree: Bachelor's Degree or Master's Degree.
- Discipline(s):
- Computer, Information, and Data Sciences (<a href="#" data-bs-toggle="popover" tabindex="0" role="button" data-bs-title="Computer, Information, and Data Sciences" data-bs-content="
- Artificial Intelligence (including Robotics, Computer Vision, Human Language Processing, and Machine Learning)
- Computer Science - Languages and Systems
- Computer Science (general)
- Computer Systems Analysis
- Computer Systems Design (including Signal Processing)
- Data Science
- Databases, Information Retrieval, and Web Search
- Information Science and Technology
- Software Engineering
- Environmental and Marine Sciences (1 )
- Life Health and Medical Sciences (2 )
Affirmation
I certify that I have not previously been employed by CDC or by a contractor working directly for CDC. I understand that CDC does not permit individuals with a prior employment relationship with CDC or its contractors to participate as trainees in the ORISE program. (Exceptions may be granted for individuals who, since the previous CDC employment, have obtained a new STEM degree which necessitates training in a new field.)