Computational Astrophysics PhD
University of Cologne. Large-scale data analysis, scientific computing, and ML for spectral classification of stellar populations.
Background and expertise
From PhD to applied AI, on both sides of the leap.
I made this exact transition myself, then built the system to help other STEM PhDs do the same.
AI and ML Lecturer
Fresenius University of Applied Sciences. Teaching ML to engineering students, which forces clarity in explaining what hiring managers actually want.
Published Researcher
Peer-reviewed astrophysics and co-authored AI papers. I know how academic output reads and how to translate it into language industry recruiters actually parse.
Machine Learning Engineer
Access e.V., Aachen. Building physics-informed ML systems for aerospace manufacturing. Production pipelines that ship.
Both Sides of the Transition
5 years in academic research, now industry ML. Lived the transition, know what stays the same and what has to change.
Germany Since 2019
German recruiters, German ATS, German salary bands, German interview rituals. Not theory, lived experience.
Ready to make the transition?
Pick the depth of support that fits where you are. Or start with the free diagnostic to find your bottleneck first.