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pollution, an existential threat to Europe and the world, impacts the safety, comfort and health of humans and vegetation. It is the largest environmental cause of multiple mental and physical diseases and of
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software
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consortium-based tasks related to the 6G-Life project. Additionally, the methods and findings developed throughout the PhD track will be scalable and applicable to other research projects in MIRMI
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, freshwater and terrestrial (invertebrate) ecology, time series analyses, multiple stressors responses, and conservation (see https://www.nature.com/articles/s41586-023-06400-1 for an example). Your tasks
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property prediction, modern artificial intelligence methods, molecular dynamics, and interdisciplinary research, this is your chance to be part of an exciting journey at the forefront of science and
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems