IAESTE Internships

Location

India

Internship type

ON-SITE

Reference number

IN-2026-B1428-KU

Students Requirements

General discipline

Mechatronics
Robotics and Automation

Completed Years of Study

3

Fields of Study

General

Languages

English Excellent (C1, C2)

Required Knowledge and Experience

-

Other Requirements

The intern should have knowledge related to Python, Machine learning and Data processing

Work Details

Duration

16 - 16 Weeks

Within These Dates

04.01.2027 - 14.05.2027

Holidays

NONE

Work Environment

-

Gross pay

10000 INR / month

Working Hours

40.0 per week / 8.0 per day

Living Lodging

Type of Accommoditation

IAESTE- LC KARUNYA

Cost of lodging

5000 INR / month

Cost of living

8000 INR / month

Work Offered

Additional Info

1. The option to work from home is available for this offer. In this case, the available dates for the internship are from Jan 2026 - April 2026 and there will be no stipend provided.However, if the intern chooses to work at the employer's location, a stipend will be provided based on the dates specified in the 'Work Offered Field'.2. The intern is required to fill out the attached declaration form to confirm their preferred mode of internship.

Work description

AI-Powered Crop Disease Prediction and Smart Farming SolutionsOverview: This internship centers on building an advanced AI-driven platform to predict and manage crop diseases, enhancing agricultural productivity and sustainability. By integrating satellite imagery, weather data, and sensor-based crop health indicators, interns will design predictive models that generate real-time recommendations, enabling farmers to act proactively and minimize crop losses effectively.Objectives:1)Design, implement, and optimize AI and machine learning algorithms for accurate crop disease prediction.2)Collect, clean, and analyze agricultural datasets from multiple sources including imagery, weather, and soil sensors.3)Develop and integrate a farmer-friendly interface that delivers alerts, preventive measures, and adaptive management strategies.Outcomes:1)Acquire practical knowledge of AI applications in agriculture and precision farming.2)Gain experience in predictive modeling, data handling, and sustainable decision-making.3)Develop problem-solving and system design skills tailored to real-world agricultural challenges.Intern's Responsibilities:1)Gather and preprocess agricultural datasets for predictive analysis.2)Train, validate, and refine AI models for accurate disease detection.3)Collaborate with experts and farmers to test, evaluate, and improve system usability.

Deadline

27.03.2026