Research Intern in Medical Image analysisAt — Cedars-Sinai Medical Center
As an Research Intern, you will collaborate with research engineers, AI scientists, and clinicians on developing advanced deep learning methods for medical image analysis. This internship provides a unique academic research experience, where you will design and test hypotheses, explore novel architectures, and engage directly with cutting-edge challenges in AI for healthcare. You will be mentored by experienced researchers, gain exposure to rigorous experimentation, and contribute to work aimed at real-world clinical impact. Ideal candidates bring knowledge of deep learning or machine learning, strong analytical skills, and the curiosity to read, understand, and implement state-of-the-art research.
Posted by 08/19/25
#Foundations & Onboarding -Orientation to the lab’s research focus and ongoing projects. -Introduction to medical imaging fundamentals and clinical context. -Hands-on tutorials on tools, datasets, and workflows used in the lab. #Technical Training -Deep learning frameworks (e.g., PyTorch, TensorFlow) with a focus on image recognition and segmentation. -Best practices in data preprocessing, augmentation, and annotation for medical imaging. -Model training pipelines, hyperparameter optimization, and performance evaluation. -Exposure to reproducible research practices: version control, experiment tracking, and documentation. #Research Methodology -Guidance on reading and critically evaluating academic papers. -Training on hypothesis formulation, experimental design, and statistical evaluation. -Mentorship on translating research into publishable results and potential clinical applications. #Mentorship & Collaboration -Weekly one-on-one mentorship sessions with research engineers or scientists. -Group seminars, journal clubs, and progress discussions. -Feedback and coaching on both technical work and scientific communication (reports, presentations, publications).
The internship is fully remote or conducted in a standard office/computer lab environment. No direct handling of patients, clinical equipment, or hazardous materials is involved.
Interested students should apply by contacting the main point of contact directly via email.
| Hours | Duration |
|---|---|
| 8 | hours per week |