IAESTE Internships

Location

United Arab Emirates

Internship type

ON-SITE

Reference number

AE-2026-52-RISE

Students Requirements

General discipline

Computer Science / Informatics
Economics
Business
Management and Marketing
Industrial Engineering / System Engineering

Completed Years of Study

2

Fields of Study

Data Science
Artificial Intelligence
Machine Learning
Business Administration
Management and Operations
Logistics

Languages

English Excellent (C1, C2)

French Good (B1, B2)

Required Knowledge and Experience

-

Other Requirements

The candidate should be able to study and analyze logistics systems from economic, environmental and operations perspectives.A good level of French would also be accepted but the candidate should have good writing skills in English.

Work Details

Duration

12 - 16 Weeks

Within These Dates

01.09.2026 - 31.12.2026

Holidays

NONE

Work Environment

-

Gross pay

3000 AED / month

Working Hours

36.0 per week / 9.0 per day

Living Lodging

Type of Accommoditation

IAESTE UAE

Cost of lodging

900 AED / month

Cost of living

3000 AED / month

Work Offered

Additional Info

The start date is fixed at either 1-Sep-26 or 1-Oct-26.Please read the attached document and follow the instructions rigorously.

Work description

Research Group: Sustainable Engineering Asset ManagementResearch Center: Sustainable Systems, Technologies & Infrastructure Research Center (SSTIRC)The candidate is expected to work on a research project on Sustainable supplier and transportation network design: modeling and optimization of the economic, social and environmental aspects.The project aims at evaluating the environmental and social sustainability of purchased products using multi-criteria decision-making (MCDM) so that supply chains and in particular transportation operations are assessed in terms of their environmental and social sustainability analysis.This helps develop optimization models in order to select the suppliers and route the vehicles while considering the three sustainability pillars.The project is run by a team of faculty who specialize in the area of supply chain management, sustainability, optimization and machine learning.

Deadline

11.03.2026