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include sputter deposition and in-situ surface analysis techniques such as RHEED, AES and XPS. Part of the work is also to optimize the workflows in this laboratory in collaboration with the team. Your
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. • Systematically optimize substrate preparation, sample mounting and thermal contact, gas purity, growth temperature, and related process conditions. • Characterize grown material using techniques such as x-ray
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analyses, model evaluation, and interpretation of findings Investigate and optimize user experience and objective performance of AI systems in healthcare and medical applications together
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design specific constructs to edit transcription factor genes and their target promoters, and analyse the effects of optimized gene expression regulation on plant performance under optimal and field-like
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system serving as a real-world lead-optimization case study. The successful candidate will play a central role in the computational and AI components of the project and work closely with our international
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Research Scholar to join in research efforts of interest to its faculty. Domains of interest include nonlinear partial differential equations, computational fluid dynamics and material science, dynamical
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the energy sector Start date: 1 January 2027, or as soon as possible thereafter. The research projects You will be part of national and international funded projects focusing on the development of next
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intelligence-driven approaches to industry challenges, such as warehouse management, ocean freight optimization, and reshoring high-technology industry sectors such as semiconductors and electric vehicles
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interaction research. The postdoctoral researcher will contribute to the design and optimization of biomaterials, their biological characterization and the functional validation of the developed models
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world