The efforts in DSTrain are aligned with the primary goal of the European Green Deal stating that Europe shall be the first climate-neutral continent by 2050. Through the multitude of innovative ongoing research activities at the MN Faculty and our associated partners, the DSTrain programme offers a unique opportunity to support projects with a strong focus on sustainability and the green transition.
Data science and computing play an important role in the implementation of the green transition of society. Research related to sustainability is a prioritised area at the MN Faculty, and many of our researchers are involved in projects motivated by this. Examples include physicists working with sustainable solar cell technology, researchers at the Technology Systems department developing sustainable batteries, and mathematicians, statisticians and computer scientists researching the production and distribution of renewable energy.
Our understanding of climate changes is based on huge computational models capturing numerous physical phenomena on how the Earth´s atmosphere behaves and develops based on natural and human-made impact. The Intergovernmental Panel on Climate Change (IPCC) derives crucial findings and recommendations through thorough data analysis and high-performance computing. In the pursuit of a sustainable future, machine learning, artificial intelligence, and edge computing are becoming increasingly prevalent. These technologies contribute to the interpretation of environmental data, enhance the efficiency of weather-dependent energy generation, and improve the accuracy of climate predictions.
In addition to machine learning algorithms, artificial intelligence and edge computing are equally crucial in addressing fundamental aspects related to the efficient and accurate representation of knowledge. Furthermore, data management, including efficient data sharing, data curation, and structuring large datasets, is essential. Advances in digital twin technologies, robotics, and quantum computing will also contribute to shaping the green transition. As the utilization of machine learning algorithms and artificial intelligence systems becomes more prevalent, it is crucial to consider questions regarding uncertainty, explainability, and ethical implications.
Research Themes
All DSTrain research projects will be focused on interdisciplinary themes and the integration of computational methods will be essential. A fundamental principle of the DSTrain programme is that ground-breaking and innovative results are achieved through the collaboration of data science and natural sciences. It is crucial that this principle is clearly reflected in the project description. The postdoctoral fellows will be encouraged to develop their individual-driven research projects, ensuring academic freedom and scientific independence.
Detailed descriptions of the available research themes, as well as contact information for each, can be found on our website under Research Areas, sorted by the following categories: Astrophysics, Biosciences, Chemistry, Geosciences, Informatics, Mathematics, Pharmacy, Physics, and Technology Systems.
Applicants are required to formulate their own research projects within these themes and must specify the theme to which their project belongs.