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Hamburg University of Technology

Hamburg, Hamburg, Germany

Master of Science (M.Sc.) in Computational Methods and Machine Learning in Engineering

Original title: Computational Methods and Machine Learning in Engineering

English4 semesters (2 years)No Tuition / Semester Fee OnlyHamburg

This master's program delivers interdisciplinary skills in numerical modeling, machine learning, and simulation methods to address complex engineering challenges and supports careers in research and industry innovation.

Overview

Why this program?

English-friendly instruction
No tuition fees or semester-fee only
On Campus
Engineering & Technology
Interdisciplinary curriculum
Master of Science (M.Sc.) in Computational Methods and Machine Learning in Engineering

Program summary

Good fit, outcomes, and skills

Best for

Those targeting careers in advanced engineering research and innovation

Career outcomes

  • Computational engineer
  • Machine learning specialist
  • Research scientist
  • Simulation analyst
  • Industry innovator

Skills you will learn

  • Numerical modeling techniques
  • Machine learning applications
  • Engineering simulations
  • Interdisciplinary problem solving
  • Programming and data analysis

Admissions

Requirements at a glance

Admission typeRestricted Admission
RequirementsBachelor's degree in engineering, applied mathematics, or computational engineering; strong background in mechanics and mathematics; basic programming skills; English proficiency
DeadlineDecember 1 – February 1
LanguageEnglish
Free orientation

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Tuition & costs

What to budget for

TuitionNo Tuition / Semester Fee Only
FeesSemester fee may apply
Living costsApprox. EUR 850-1,200/month

Careers

Where this can lead

Computational engineer
Machine learning specialist
Research scientist
Simulation analyst
Industry innovator

University

Hamburg University of Technology

Hamburg University of Technology is located in Hamburg, Hamburg, Germany. Open the official program page for the latest application details, deadlines, and documents.

Program data is collected from public university sources and may be incomplete or outdated. Always verify deadlines, fees, and admission requirements on the official university website.

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