Masterstudium Chemie-Ingenieurwesen – Technische Universität München

Programme structure

Note on the FPSO version

This structure follows the FPSO of 2 April 2026 (for students starting from winter semester 2026/27). There is also the FPSO in the version of 25 Nov 2021 (for students starting before winter semester 2026/27). Please check that the version used here applies to you; as a rule it depends on when you started your studies. Changes from 2021: 30 instead of 40 mandatory credits, orientation 20 instead of 15 and free subject selection 10 instead of 5 credits, changed orientation categories. Switch to the other version

Master's Thesis–

Mandatory Modules–

At least one of the foundation modules (#) must be passed by the end of the 2nd semester.

Elective Modules: Orientation–

Bioprocessing–Chemical Process Technology–Energy Process Technology–Catalytic and Electrochemical Process Engineering–Modeling and Data Science–

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Elective Area: Free Subject Selection–

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Total–

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Modules

4 results

Elective Modules: Orientation4

Chemical Engineering Design Course (with UniSim Design)No ratings for this module yet.Modeling and Data ScienceIn the internship you will learn to set up, carry out and evaluate process simulations with Aspen Plus® for process engineering questions. In the end you will be able to create simulations of existing thermal processes, analyze their sustainability and economic viability, and develop optimization approaches.4 ECTSruns this semesterMW0290 Einführung in Machinelles Lernen in den MaterialwissenschaftenNo ratings for this module yet.Modeling and Data ScienceThe course provides the fundamentals of machine learning with a focus on applications in materials science. You will learn typical methods (e.g., clustering, regression, classification, deep learning, Bayesian optimization), work with materials science datasets, and practice practical implementation in Python notebooks. In the end you will be able to select appropriate representations and methods, evaluate models, and carry out a small ML project in materials science.5 ECTSruns this semesterNAT3037 Modellbildung in der Chemischen ReaktionstechnikNo ratings for this module yet.Modeling and Data ScienceYou will learn to describe and analyze reaction engineering processes and industrial reactors with mathematical models. The module combines fundamentals from thermodynamics, heat and mass transfer, reaction engineering and catalysis with methods of data analysis, numerical analysis, multiscale modelling and statistics as well as MATLAB programming. In the end you will be able to develop models, solve them numerically and evaluate the effects of heat and mass transport on reactor design.5 ECTSruns this semesterCH0166 Datenanalyse und VersuchsplanungNo ratings for this module yet.Modeling and Data ScienceYou will learn fundamentals of statistics and probability theory as well as methods of experimental design. Building on this, procedures of data analysis (e.g., cluster methods, principal component analysis, exploratory factor analysis) and model types for structure optimization such as Bayesian networks are covered. In the end you can analyze data from large data sets and create simple model structures for parameter identification in biomechanical/biochemical networks.5 ECTSno date this semesterMW2248

1 more module matches, but it is taught in German. Show it

Modellierung verfahrenstechnischer ProzesseNo ratings for this module yet.Modeling and Data ScienceDu lernst die Grundlagen der Programmierung in MATLAB und die objektorientierte Modellierung verfahrenstechnischer Prozesse. Am Ende kannst du MATLAB-Code erstellen, Fehler analysieren, eigene Klassen entwerfen und verfahrenstechnische Modelle (z. B. Phasengleichgewicht mehrkomponentiger Gemische) implementieren und lösen.5 ECTSruns this semesterMW2390