SULI– DSL –Suleman (Lavelle), Hasan (Vincent)– 2.13.26

Argonne National Laboratory • Lemont, IL

6d

About The Position

Medicine in the digital era generates a large amount of data. Effective and efficient analysis on these data is necessary for the success of biomedical research. Our research focuses on the development and application of artificial intelligence (machine learning and deep learning) on various kinds of biomedical data, including genomic data, clinical information, medical images, chemical data, and pharmacological data. We develop algorithms and software for analyzing these data to help multiple aspects of biomedical research and clinical practice, such as study of disease mechanism, design of treatment plan, computer-aided disease diagnosis, and prediction of disease prognosis. One example project is a collaboration between the Argonne National Laboratory and the National Cancer Institute to develop and evaluate machine learning models for predicting the response of drugs on cancer patients and animal models. Another example project is a collaboration between the Argonne National Laboratory and the Mayo Clinic for predictive analysis of digital pathology images for disease diagnosis, prognosis, and treatment design. Education and Experience Requirements The entirety of the appointment must be conducted within the United States. Must be 18 years or older at the time the appointment begins. Applicants must be: ‒Currently enrolled in undergraduate or graduate studies at an accredited institution ‒Graduated from an accredited institution within the past 3 months; or ‒Actively enrolled in a graduate program at an accredited institution

Requirements

• The entirety of the appointment must be conducted within the United States.
• Must be 18 years or older at the time the appointment begins.
• Applicants must be: ‒Currently enrolled in undergraduate or graduate studies at an accredited institution ‒Graduated from an accredited institution within the past 3 months; or ‒Actively enrolled in a graduate program at an accredited institution

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed