IN-2025-D1101-MJ
Location
India
Internship type
ON-SITE
Reference number
IN-2025-D1101-MJ
General discipline
Bioengineering/Biomedical Engineering
Computer Science / Informatics
Completed Years of Study
2
Fields of Study
Languages
English Excellent (C1, C2)
Required Knowledge and Experience
-
Other Requirements
-
Duration
7 - 8 Weeks
Within These Dates
06.05.2025 - 27.09.2025
Holidays
NONE
Work Environment
-
Gross pay
16000 INR / month
Working Hours
40.0 per week / 8.0 per day
Type of Accommoditation
IAESTE
Cost of lodging
8500 INR / month
Cost of living
16000 INR / month
Additional Info
Work description
Mathematics & Statistics Intern : Title Of The Project : Epidemiological Models: A mathematical and Machine learning perspective Work Description: 1.This project is about to learn epidemiological models, their modeling and simulation, epidemiological data analysis and visualization. This project aims to build models for forecasting the epidemic (infection like COVID 19 /rumor) as well as the epidemic/rumor source detection through machine learning techniques. 2. This approach is useful for interns having interest in modeling and simulation, epidemiology and data science persons. This project is useful for understanding the phenomena of infection/rumor spreading, its forecast and early detection strategies for proper intervention and control strategies for emergencies. 3. Data Collection: Gather epidemiological and demographic data from various sources including Data Preprocessing with clean, normalize, and structure data for analysis. Expected Outcome : 1. The project aims to enhance the accuracy of epidemiological models by integrating mathematical and machine learning approaches, improving disease prediction and control strategies. 2. The intern will create a report of the whole study. We will support the intern the publish the completed work in the form of a research paper in some reputed journal. 3. The intern’s role includes data collection, model implementation, algorithm optimization, and interpreting model results for public health insights.
Deadline
30.04.2025