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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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focus on distributed acoustic sensing on pre-existing telecom fiber networks, wavefield analysis, structural and geophysical interpretation, multi-modal data fusion, and lab-scale and field experiments
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telecom fiber networks. The role will focus on ambient and anthropogenic seismic noise for urban subsurface characterization, seismic source characterization, geophysical imaging, and environmental
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at least one of the following fields: approximation of neural networks, convergence of Langevin/MC sampling, analysis and algorithm design of interacting particle systems, operator learning, regularity
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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for existing commercial products. The work will involve numerical investigation of two-phase flows over louvre panels and experimental verification as well as optimal design by using neural network techniques
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world models with generative AI and theory-informed neural networks. Job Responsibilities: Conducting theoretical and empirical studies on economic world models, with a strong emphasis on critical finance
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, subjective evaluation, and AIoT implementation. Key Responsibilities: Writing, debugging, optimizing and testing of source code with an emphasis on audio applications Maintenance and improvement of existing
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hands-on experience in specific scope Familiarity with required scope (e.g. national codes and standards) Good written and oral communication skills (if applicable) Proficiency in hard skills / job
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, satellite communication systems, or energy engineering for wireless networks. Experience securing research funding, managing research programs, and building academic partnerships. Experience with embedded