Matthias Steiner

Provide (environmental) data analysis and modeling services to clients, enabling them to extract meaningful insights and make informed decisions. Teach environmental data processing and analysis concepts at various levels. Design and implement science outreach initiatives to promote environmental awareness and public engagement with research.

Developed and optimized computational models to describe complex physical systems, combining analytical and numerical methods for data-driven decision-making. Designed and implemented physics-based modeling and inversion algorithms using Python, enhancing performance and scalability across multiple research applications. Applied advanced data processing and visualization techniques to extract insights from multidimensional datasets. Contributed to project coordination, supervision, and teaching, fostering interdisciplinary collaboration and knowledge transfer. Engaged in scientific outreach and communication, translating technical results into accessible insights for academic, industrial, and public audiences.

Designed and implemented inversion algorithms and data analysis workflows for interpreting geophysical and environmental datasets, improving model accuracy and computational efficiency. Developed open-source, platform-independent software for geoscientific data processing using Python, promoting reproducibility and collaborative development. Managed GIS-based projects within interdisciplinary research initiatives, integrating spatial data and metadata management tools such as QGIS. Published and presented research findings at international conferences and in peer reviewed journals, strengthening scientific communication and dissemination skills. Conducted lectures, workshops, and student supervision to teach course content, guide research projects, and coordinate student activities.