Computational Methods and Machine Learning in Engineering is a multidisciplinary field and hence, graduates are well-equipped for a wide range of careers across industries. Some prominent job roles include:
- Simulation Engineer – Develops and runs simulations to test designs in fields like aerospace, automotive, or civil engineering, reducing the need for physical prototypes.
- Computational Fluid Dynamics (CFD) Engineer – Specializes in simulating fluid flows, often working in aerospace, automotive, or energy industries.
- Structural Analyst – Uses numerical methods to analyze the structural integrity of buildings, vehicles, or machinery.
- Software Developer – Designs and develops scientific and engineering software, particularly tools that perform simulations or data analysis.
- Machine Learning Engineer – Builds and deploys machine learning models, benefiting from strong programming and mathematical modeling skills.
- High-Performance Computing (HPC) Specialist – Works on optimizing software to run efficiently on supercomputers, often in research or national labs.
- Research Scientist – Conducts academic or industrial research using computational methods to investigate scientific or engineering problems.
These roles exist in industries such as aerospace, automotive, biomedical engineering, energy, defense, tech, and academia. A strong foundation in coding, numerical methods, and domain-specific knowledge makes computational engineering graduates valuable assets in both technical and research-driven environments.
Top 10 employers of TUHH graduates:
- Airbus
- Lufthansa Technik
- NXP
- Siemens Gamesa
- Tesa
- Nordex
- Beiersdorf
- DLR
- Siemens
- DNV
[source: Alumni Report 2024]
What our industrial partners say:
“Simulation and modeling methods are used on a daily basis at tesa. Our expertise in continuum mechanics, finite element analysis, mathematical optimization, and machine learning allows us to develop exceptional solutions for our customers, contributing to tesa’s success.” - Dr. Nils Hendrik Kröger, Lab Manager Simulation at tesa.
“Mathematics is the backbone of innovation in my work. It enables the development of advanced simulation and optimization algorithms, which are essential for creating precise and efficient solutions to complex engineering challenges.” - Dr. Iryna Kulchytska-Ruchka, Research Engineer at Robert Bosch GmbH