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developing new explanation methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as
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theories and models. This project aims to develop new insights into how bedrock incision processes interact with geological and climatic factors (i.e. spatially variable uplift, shield building, mega
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evolving systems of evaluation influence recognition, diffusion, and legitimacy. The focus is on advancing theory through conceptual reasoning, analytical approaches, and engagement with novel forms of data
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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0.8 fte - 1 fte Introduction Are you passionate about understanding the transformation of cities over time? Do you want to find out which kind of governance arrangements drive or hinder
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targeted professional development programs For questions or in case of technical difficulties, contact us at rtg3120 at tu-dresden.de . For more information about RTG 3120: www.dresdencondensates.org
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about the PhD programme is available at: https://www.soclaw.lu.se/sites/soclaw.lu.se/files/2021-06/ASP_rättssociologi_forskarutbildning_20201126.pdf Qualifications Requirements: A master’s degree in
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18 Oct 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Mathematics » Probability theory Mathematics » Statistics Researcher Profile First Stage
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of the Khovanov–Seidel representation in new cases, using Garside-type approaches. Developing extensions of Garside theory to the case of infinitely many atoms may also be of interest and will rely on the study of
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seeking a talented and motivated researcher to join our team as a permanent Researcher in autonomous AI 6G Systems. We are looking for candidates who are passionate about exploring the intersection