IAESTE Internships
IN-2026-D1118-MJ
Computer Science / Informatics in India
Location
India
Internship type
ON-SITE
Reference number
IN-2026-D1118-MJ
Students Requirements
General discipline
Computer Science / Informatics
Completed Years of Study
1
Fields of Study
General
Languages
English Excellent (C1, C2)
Required Knowledge and Experience
-
Other Requirements
Coding in Python, Fluency in English, Trainee required to bring laptop for entire training duration.
Work Details
Duration
6 - 10 Weeks
Within These Dates
06.05.2026 - 27.09.2026
Holidays
NONE
Work Environment
-
Gross pay
16000 INR / month
Working Hours
40.0 per week / 8.0 per day
Living Lodging
Type of Accommoditation
IAESTE
Cost of lodging
8500 INR / month
Cost of living
16000 INR / month
Work Offered
Additional Info
Work description
Artificial Intelligence InternProject Title: Medical Data Generation & Explainable AIProject Overview:This project focuses on generating high-quality synthetic medical data and applying explainable AI (XAI) techniques to enhance the interpretability of AI/ML models in healthcare. The intern will work on creating synthetic patient records, imaging datasets, and clinical notes to address the challenges posed by limited annotated datasets for training AI models. The project also involves applying XAI methods such as Grad-CAM, LIME, SHAP, and Integrated Gradients to analyze both visual and tabular medical data. By highlighting critical regions in MRI and X-ray scans, the project aims to improve disease detection accuracy while providing interpretable insights for clinicians. The study bridges data generation, AI modeling, and explainable analytics, contributing to reliable and transparent AI solutions in medical applications.Expected Outcome:• Synthetic medical datasets for training AI/ML models.• Application of explainable AI techniques on imaging and tabular data.• Documentation of model performance, XAI analyses, and key findings.• Presentation summarizing insights, critical region identification, and potential clinical impact.
Deadline
26.03.2026
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