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Laying the mathematical and methodological foundations to enable future generations of mathematicians to continue developing machine learning and scientific data analysis – that is the purpose of a new research-oriented course at Heidelberg University. The master’s program “Mathematics of Machine Learning and Data Science”, taught in English, is starting in the 2025/2026 winter semester and is particularly intended for graduates of bachelor courses in mathematics.
Press Release
Heidelberg, 21 March 2025
New Master’s Program: Expanding on Machine Learning and Scientific Data Analysis
Research-oriented mathematics program to start in winter semester 2025/2026
Laying the mathematical and methodological foundations to enable future generations of mathematicians to continue developing machine learning and scientific data analysis – that is the purpose of a new research-oriented course at Heidelberg University. The master’s program “Mathematics of Machine Learning and Data Science”, taught in English, is starting in the 2025/2026 winter semester and is particularly intended for graduates of bachelor courses in mathematics. It is based in the Faculty of Mathematics and Computer Science, coordinated by the Institute for Mathematics and will be carried out in cooperation with the Interdisciplinary Center for Scientific Computing. The closing date for applications is 15 May 2025.
“Machine learning and data science are currently revolutionizing the sciences. This equally concerns basic research to better understand established methods, such as the learning-based analysis of data, as well as projects to apply these methods in by now almost all branches of science,” underlines Prof. Dr Christoph Schnörr from the Institute for Mathematics of Heidelberg University. This is where the new consecutive, four-semester master’s program starts: it imparts an in-depth understanding of how pure mathematics and applied mathematics interact, in order to innovatively expand on the methodology of machine learning and scientific data analysis. To this effect, the course connects up topology, differential geometry and dynamic systems with statistics, optimization, numerics and functional analysis.
“Compared to the regular mathematics master’s, this program is extremely interdisciplinary in approach. We see this, for example, in the lecture series for the first semester, which gives a broad overview of core fields of mathematics,” says Prof. Schnörr. Students will work on the implementation and application of models from the lectures in a data science lab. The option to spend a semester abroad offers the opportunity to try out team work at the international level, the Heidelberg mathematician adds. Specialization modules extending over the two years will prepare the students for their master’s thesis.
Apart from specialist qualifications, students enrolled in the master’s program “Mathematics of Machine Learning and Data Science” will acquire core competences in analytical and structural thinking, scientific problem-solving and interdisciplinary collaboration. This will equip the graduates for doctoral positions in Germany and abroad, and also for research-oriented posts in industry, particularly in the area of developing methods for addressing problems in machine learning and scientific data analysis.
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http://www.uni-heidelberg.de/en/study/all-subjects/mathematics-of-machine-learni... – Master’s program “Mathematics of Machine Learning and Data Science”
http://www.mathinf.uni-heidelberg.de/en – Faculty of Mathematics and Computer Science
https://typo.iwr.uni-heidelberg.de/home – Interdisciplinary Center for Scientific Computing
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