Scientific Software Development for Research and Education
Quellcode 360 GmbH develops custom software solutions for science, research and data-driven projects. Our specialization in scientific software stems from deep roots in academic research – particularly in astronomy, astrophysics and high-performance data analysis.
This focus is backed by the academic experience of Dr. Johannes Puschnig, a former researcher in astrophysics and radio astronomy. His work involved processing and analyzing massive datasets from telescopes and experiments, using techniques such as spectral analysis, Fourier transforms (FFT), and statistical modeling.
What We Build
- Custom tools for data analysis and model fitting
- Big Data pipelines for physical sciences
- Web-based platforms for research and research collaborations
- Machine learning and training of AI models
- Interactive tools for scientific visualization
Technical Stack
- Languages: Python, C, C++, JavaScript, SQL
- Libraries: numpy, numba, pandas, scipy, matplotlib, astropy
- Frameworks: Flask, Django, React, Node.js
- Scientific tools: MCMC (emcee), FFT, NLTE models, HDF5, FITS, PySME
- Deployment: Docker, GitHub Actions, REST APIs
Read more about our complete tech stack (in German only).
Our tools are used in active research, including large-scale parameter estimation and chemical abundance analysis. One example is webSME, a modern full-stack platform for stellar spectroscopy - developed as part of academic collaborations and now freely available.
With our experience in transforming scientific methods into robust, user-friendly software, we support universities, research teams and science-driven companies in making their data accessible and insightful.
Use Case: webSME
- Online analysis tool for high-resolution stellar spectra
- Built with Python, Flask, Celery and Redis
- Includes MCMC (Monte Carlo Markov Chain) sampling
- Optimized for large wavelength ranges
We also offer consulting and development partnerships to create new tools for research fields such as Earth observation, medical imaging, and time-series analysis. Scientific programming is not just a service – it is our core competence.
Wie können wir helfen?
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