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on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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Description FlexCAT is an international Marie Skłodowska-Curie Actions (MSCA) Doctoral Network focused on developing innovative strategies to study and target intrinsically disordered regions (IDRs) in proteins
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for Integrated Terrestrial NTN 6G Networks Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The
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Imperial College London is recruiting two Doctoral Candidates (DCs) to work in the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network (DN) "SPARK" (HORIZON-MSCA-2025-DN-01-01), devoted to spatiotemporal
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available in Germany within the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network TRILOGY, funded under Horizon Europe. The selected doctoral candidate will work on an interdisciplinary research project
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new theoretical approaches for understanding stability, generalization, and feature learning in large-scale neural networks. Further details and application instructions are available at: https
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the principles of the European Charter for Researchers, the Code of Conduct for the Recruitment of Researchers, and the Doctoral Network mobility rules. The process will follow an open, transparent, merit-based
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Network ReDiLEEP (https://redileep.eu/ ). ReDiLEEP brings together leading universities, research institutes, and non-academic partners across Europe and beyond to advance response diversity research and
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | about 2 hours ago
coding, skills in statistical data analysis (especially social network analyses), and programming (e.g., in R). More important than specific prior experience is enthusiasm for learning and the demonstrable
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. Field research: A major component of the PhD will involve intensive in-situ field measurements in selected sites of the TIF-CER field network and integration of data from across the field network