I am a recent M.Sc. graduate in Quantum Information Science from the University of Copenhagen (UCPH) and Technical University of Denmark (DTU), with a passion for translating complex mathematical frameworks into practical, production-ready software. My background spans quantum computing, numerical optimization, data science, and scientific computing.
I thrive on moving from idea to execution, experimenting with emerging technologies, and working across disciplines. What motivates me most is building solutions that people actually use.
- Implementing Gaussian Boson Sampling for binary optimization (based on a recent paper) to demonstrate quantum-inspired algorithms for real-world problems.
- Building a portfolio of Python projects that showcase my skills in numerical optimization, data pipelines, and scientific computing.
- Applying for roles as an Algorithmic Software Engineer, AI Developer, or Technology Advisor in quantum technologies.
- Advanced quantum algorithms and their applications in optimization and chemistry.
- Best practices for production-ready Python code, including testing, CI/CD, and containerization.
- The intersection of quantum technology and defense applications, including NATO DIANA initiatives.
- Opportunities to apply my skills in quantum-inspired algorithms and software engineering.
- Collaboration on open-source projects in quantum computing, AI, or scientific computing.
- Roles where I can bridge the gap between research and practical software development.
- Quantum Information Science and quantum algorithms (VQE/QAOA, Qiskit, Pennylane).
- Python development (NumPy, SciPy, PySCF, Pandas).
- Numerical optimization and linear algebra.
- My M.Sc. thesis on Optimised Virtual Orbital Space (OVOS).
- My experience with the EFEQT programme and international quantum conferences.
- Email: tobias.clausen1@gmail.com
- LinkedIn: linkedin.com/in/tobias-born-clausen-b74b26237
- GitHub: You're already here!
I participated in the QST-Hack 2025, an invitation-only hackathon at DTU, where I collaborated with an international team on a science communication challenge focused on quantum algorithms.
I am passionate about making complex technical concepts accessible to diverse audiences and believe that clear communication is as important as technical skill.
| Category | Tools |
|---|---|
| Languages | Python, C++, LaTeX |
| Libraries | NumPy, SciPy, PySCF, Pandas, Qiskit |
| Tools | Git, Docker, VS Code, Linux |
| Concepts | Numerical Linear Algebra, Optimization Algorithms, Quantum Algorithms, HPC |
| Project | Description |
|---|---|
| Optimised Virtual Orbital Space (OVOS) | Python implementation of a numerical optimizer and matrix compression algorithm from a 1987 paper. |
| Correlation-Optimized Virtual Orbitals (COVO) | Dimensionality-reduction algorithm using PCA techniques on dense matrix decompositions. |
| Agentic RAG System | Production-ready RAG system using LangChain, ChromaDB, and Ollama. Demonstrates API design and data pipeline development. |
- Secure a role where I can apply my Python and algorithmic skills to solve real-world problems.
- Continue developing my expertise in quantum-inspired algorithms and software engineering.
- Contribute to the growing quantum technology ecosystem in Denmark and Europe.
For more details on my experience and education, please see my LinkedIn profile or contact me directly.
Thanks for visiting my GitHub profile!