Applied Geosciences – Computational Geology and Geophysics (CGG) (MSc)

This specialisation in Computational Geology and Geophysics is one of five streams within the MSc Applied Geosciences programme (the others are Applied Mineralogy and Crystallography, Energy and Mineral Resources, Field-Based Geosciences, and Geoengineering). Taught in English, the CGG track focuses on using advanced computational methods and geophysical techniques to study the Earth. The programme takes an interdisciplinary approach, combining theoretical fundamentals with practical, project-based learning so students can tackle real-world problems in areas such as sustainable resource exploration, renewable energy, and geodata science.

The curriculum trains students to analyse complex geological datasets, model subsurface structures, and interpret a variety of geophysical measurements. Core topics include basic geoscientific principles, geothermics, applied geophysics, programming, spatial data analysis and visualisation, statistics, numerical modelling, and applications of artificial intelligence. Practical work and hands-on projects are emphasised to build transferable skills that are relevant to both industry and research settings.

Students follow a set of compulsory modules to ensure solid foundations and choose from elective courses to tailor their profile toward academic, industrial, or interdisciplinary careers. The programme concludes with a Master’s thesis on a topic selected by the student, allowing independent research and specialization. Graduates are prepared for roles in academia, industry, and research institutions, and for collaborative work across disciplines.

Key programme components / requirements

• Part of the MSc Applied Geosciences offering alongside four other specialisations
• Taught in English with a mix of compulsory and elective modules
• Core curriculum: geoscientific fundamentals, geothermics, applied geophysics
• Computational and analytical skills: programming, spatial data analysis and visualisation, statistics, numerical modelling, AI
• Emphasis on hands-on projects addressing practical problems (e.g., resource exploration, renewable energy, geodata science)
• Programme ends with a student-selected Master’s thesis for independent research or application

You can download the current, official course curriculum from the program page at: https://www.fgeo.rwth-aachen.de/cms/geowissenschaften-und-geographie/Studium/Studiengaenge/Master-courses-of-study/Angewandte-Geowissenschaften/~cajo/Kurzprofil-des-Studiengangs/lidx/1/

This document contains the definitive structure and requirements for the Applied Geosciences – Computational Geology and Geophysics (CGG) MSc. It sets out the semester-by-semester module plan, ECTS credit allocation, examination and assessment rules, elective options, and the master’s thesis requirements. For precise module names, syllabi, and any up-to-date changes, please consult that downloadable curriculum.

By its title and as reflected in the curriculum, the programme emphasizes computational approaches applied to geological and geophysical problems. Key thematic areas covered include numerical modelling and simulation, processing and interpretation of geophysical and geological data, and methods for subsurface imaging and characterisation. The official curriculum lists the detailed learning outcomes that students must achieve—typically combining advanced computational skill development with applied field and laboratory practice and culminating in an independent research thesis.

What the downloadable curriculum provides (at a glance)

• Full module catalogue with descriptions and learning objectives
• ECTS credit breakdown and recommended semester plan
• Details on compulsory vs elective modules and specialisation options
• Examination rules, assessment formats and progression requirements
• Master’s thesis regulations, expected outcomes and credit value
• Contact information for programme coordinators and responsible institutes

If you would like, I can extract and rewrite the specific module list and stated learning outcomes from the downloadable file—paste the PDF or its text here or confirm that you want me to fetch and summarize it.

Graduates are prepared for careers in academia, research institutions and industry sectors that rely on subsurface modelling and geodata analysis — including resource exploration, renewable energy, environmental and geotechnical consulting, and data-driven geoscience roles. With skills in numerical modelling, geophysical interpretation and machine learning, alumni can work as computational geoscientists, geophysicists, data scientists in geoscience contexts, consultants or continue into PhD research.