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20 Jun 2026 Job Information Organisation/Company Tilburg University Research Field Economics » Construction economics Researcher Profile Recognised Researcher (R2) Application Deadline 15 Jul 2026
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more, please visit eng.aalto.fi. We are now looking for a Doctoral Researcher in Structural Health Monitoring and Condition Assessment. We are seeking a highly motivated Doctoral Researcher in Structural
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results. Where to apply Website https://system.erecruiter.pl/FormTemplates/RecruitmentForm.aspx?WebID=b285e7ed1… Requirements Research FieldOtherEducation LevelMaster Degree or equivalent Skills
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 10 hours ago
to operate a backhoe and other construction equipment. Perform other duties as assigned. Monday-Friday 8:00-4:30pm A high school diploma or an equivalent combination of education and experience from which
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of metabolism, membrane transport, cellular regulation, structural systems biology, machine learning and disease mechanisms. These positions are embedded in the transition from CeMM in Vienna to the newly founded
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environments). It bridges fundamental physics and system-level engineering. Key areas include heat and mass transfer, structural integrity, and material performance under extreme conditions. The role emphasizes
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research in areas such as Food Chemistry and Toxicology and Functional Materials and Catalysis. Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant
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total maximum of 4 years is possible. Successful candidates will join the VDS-PhaNuSpo that brings together doctoral candidates and researchers from diverse disciplines and offers a structured doctoral
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Vienna Doctoral School in Cognition, Behavior, and Neuroscience - Doctoral Positions (AUTUMN CALL 20
good ability to present and process research questions in a structured way Ability to work independently and as part of a team Publications or basic experience in scientific work and research methods
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methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and structure-aware learning; and the