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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications. Host: Helmholtz-Zentrum Hereon
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students with similar research interests discuss theoretical texts and concepts. In addition, this PhD programme includes: Elective Options (18 ECTS credits): Elective options are meant to give students
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group of 10 PhD students will join our structured training program and participate in regular scientific exchange e.g. in retreats, colloquia and in tailored workshops. Requirements Candidates should hold
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“Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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Your Job: In this PhD project, you will shape the future of power system security by harnessing exascale computing. Your research will focus on understanding and enhancing grid resilience under
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their achievements and productivity to the success of the entire institution. At the Faculty of Electrical and Computer Engineering, Institute of Solid State Electronics, Chair of Coating Technologies in Electronics
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PhDGermany Find your suitable PhD opportunity in Germany. Find your suitable PhD opportunity in Germany. Back to Overview Working LanguageEnglish LocationMünchen Application Deadline30 Jan 2026
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THE FIELDS OF: ATMOSPHERIC PHYSICS AND CHEMISTRY, ELECTROCHEMISTRY, ELECTROCHEMICAL ENERGY STORAGE (BATTERIES), ELECTRONICS, ELECTRICAL AND MECHANICAL ENGINEERING, HIGH-PERFORMANCE COMPUTING, MACHINE LEARNING