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Field
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Digital Twin predictions against real-world treatment outcomes from clinical registries. A Unique Dual-University Experience This position offers an exceptional opportunity to work across two leading
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revisiting ideas and concepts from this field for the purpose of interpretable machine learning. Pattern-based modelling, for example, cannot only be used for exploratory data mining but also for predictive
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applied mathematics in general. Mobile working A certified (Audit berufundfamilie) family-friendly work environment. Berlin is one of the most culture-rich and diverse international cities in the world. It
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this project, funded by the Swiss Federal Office for the Environment (FOEN), the occurrence of PFASs in ambient air will be investigated. Sampling a broad range of PFASs simultaneously is challenging, as is
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analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how
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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
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applied mathematics in general. Mobile working A certified (Audit berufundfamilie) family-friendly work environment. Berlin is one of the most culture-rich and diverse international cities in the world. It
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applicants will work as part of the Groeien met Groen Staal (GGS) programme, which aims to make the Dutch steel sector CO₂-neutral by 2050. Steel is crucial to modern society and plays a significant economic
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for its strength in optimization, optimal control, dynamical systems, and applied mathematics in general. Mobile working A certified (Audit berufundfamilie) family-friendly work environment. Berlin is one
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applicants will work as part of the Groeien met Groen Staal (GGS) programme, which aims to make the Dutch steel sector CO₂-neutral by 2050. Steel is crucial to modern society and plays a significant economic