Resume Mathematician in Switzerland Zurich – Free Word Template Download with AI

Name: Dr. Lena Müller

Email: [email protected]

Phone: +41 79 123 4567

LinkedIn: linkedin.com/in/lenamueller-math

Location: Zurich, Switzerland

A dedicated Mathematician with over 10 years of experience in advanced mathematical research, analysis, and problem-solving. Specializing in applied mathematics and computational modeling, my work is deeply rooted in the academic and industrial landscape of Switzerland Zurich. As a Swiss-qualified mathematician, I am committed to bridging theoretical mathematics with real-world applications that drive innovation. My expertise spans numerical methods, mathematical finance, and data science, with a strong focus on collaborative projects within Zurich’s prestigious institutions such as ETH Zurich and the Swiss Federal Institute for Technology. This resume highlights my academic achievements, professional contributions, and passion for advancing mathematical research in Switzerland Zurich.

Doctor of Philosophy (PhD) in Mathematics

ETH Zurich (Switzerland)

Graduation Date: 2015

• Dissertation: "Numerical Optimization Techniques for High-Dimensional Systems" (Advisor: Prof. Dr. Hans Fischer)
• Focus Areas: Partial Differential Equations, Computational Algebra, and Mathematical Modeling

MSc in Applied Mathematics

University of Zurich (Switzerland)

Graduation Date: 2011

• Coursework: Advanced Calculus, Probability Theory, and Mathematical Statistics
• Thesis: "Stochastic Processes in Financial Markets" (Awarded Best Thesis in 2011)

BSc in Mathematics

ETH Zurich (Switzerland)

Graduation Date: 2008

Senior Research Mathematician

Institute for Computational Mathematics, Zurich (Switzerland)

Employment Period: 2018 – Present

• Led a team of 5 researchers in developing numerical algorithms for solving complex fluid dynamics problems, contributing to projects funded by the Swiss National Science Foundation (SNSF).
• Collaborated with Zurich-based engineering firms to optimize structural designs using mathematical modeling, reducing material costs by 18% in pilot projects.
• Published 7 peer-reviewed articles in top-tier journals, including "SIAM Journal on Scientific Computing" and "Journal of Computational Physics."

Postdoctoral Researcher

ETH Zurich (Switzerland)

Employment Period: 2015 – 2018

• Focused on the development of machine learning models for predicting rare events in financial markets, aligning with Zurich’s reputation as a global hub for financial mathematics.
• Co-developed an open-source Python library (ZurichMath) used by over 2,000 researchers worldwide for numerical simulations.

Teaching Assistant & Lecturer

University of Zurich (Switzerland)

Employment Period: 2011 – 2015

• Instructed undergraduate and graduate courses in linear algebra, differential equations, and probability theory.

Research Interests

• Numerical Analysis and Scientific Computing
• Mathematical Finance and Risk Modeling
• Data-Driven Optimization and Machine Learning

Key Publications

• Müller, L., & Fischer, H. (2021). "High-Dimensional Numerical Integration Using Adaptive Sampling." *SIAM Journal on Scientific Computing*, 43(2), 891–915.
• Müller, L. (2019). "Stochastic Differential Equations in Portfolio Optimization." *Journal of Financial Mathematics*, 7(4), 301–320.
• Müller, L., et al. (2017). "ZurichMath: A Python Library for Computational Mathematics." *Computing in Science & Engineering*, 19(5), 56–63.

• Programming Languages: Python, MATLAB, R, C++, LaTeX
• Data Analysis: Pandas, NumPy, TensorFlow, Jupyter Notebooks
• Mathematical Software: Mathematica, Maple, AMPL
• Cross-Platform Tools: Git (GitHub), Docker, LaTeX Beamer for presentations

• German (Native)
• English (Fluent)
• French (Basic – B1 Level)

• SNSF Grant Recipient (2020): Funded project on "Optimization in High-Dimensional Spaces" for 3 years.
• Swiss Mathematical Society Award (2019): Recognized for contributions to computational mathematics.
• Coursera: Advanced Machine Learning Specialization (2021): Completed with distinction, focusing on mathematical foundations of AI.

Available upon request. Contact Dr. Lena Müller for details.