IAESTE Internships

Location

Austria

Internship type

ON-SITE

Reference number

AT-2024-2014GR

Students Requirements

General discipline

ENGINEERING
Other
MECHANICAL ENGINEERING
MATHEMATICS AND STATISTICS

Completed Years of Study

2

Fields of Study

Languages

English Good (B1, B2)

German Good (B1, B2)

Required Knowledge and Experience

-

Other Requirements

Interpersonal skills, Ability to work independently, self-organized, Interest in Large Combustion Engine Research

Work Details

Duration

20 - 52 Weeks

Within These Dates

15.04.2024 - 30.06.2025

Holidays

NONE

Work Environment

-

Gross pay

1850 EUR / month

Working Hours

40.0 per week / 8.0 per day

Living Lodging

Type of Accommoditation

Trainee with the help from IAESTE

Cost of lodging

350 EUR / month

Cost of living

700 EUR / month

Work Offered

Additional Info

Interview requested by the employer, due to the summer vacation period, an internship beginning September 2024 or later is preferred.We expect an internship in return from the country of the selected student.

Work description

Data analytics methods are precious tools for research on large internal combustion engines, where the foundation is laid for later series applications such as condition monitoring. In addition to in-depth exploratory analyses, advanced machine learning based modelling techniques are used. The data formats analyzed can range from engine operating data to measurements from a specific engine component/sensor (such as a fuel injector or an in-cylinder pressure transducer) to image or text data from maintenance. During the internship offered, data analytics methods will be used to work on a specific task. Details will be determined based on the intern's prior experience and interest. Regardless of the detailed task, the interns will first be given time to familiarize themselves with the technical background. As a part of a multidisciplinary team, the intern will then independently implement the data analytics methods. Throughout the internship, all work steps should be well documented and comprehensibly presented to the team.

Deadline

22.05.2024