22 finite-element-method-"Multiple" Postdoctoral positions at Aarhus University in Denmark
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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work of the research group, it will include elements of method development within sample preparation, instrumental and data analysis, quality assurance/control and semi-quantification, in the context
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to assess stakeholder needs, create PV-integrated sensors to monitor agriculture-specific stressors, model stress impacts on PV performance, and develop innovative PV tracker controls. These elements will be
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funding, and deliver on multiple projects carried out in one of the most dynamic groups in food science at Aahrus University. You will have many opportunities to connect with other research partners, and
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postdoctoral position in methods development and analysis of multi-omics and clinical data for inflammatory skin diseases. The start date is October 1st, 2025, or as soon as possible thereafter. Research context
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system. Researchers with experience in neuroscience, microbiology and immunology are welcome to apply, but it is expected that you will span multiple of these fields once established in the lab. You will
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or laboratory analyses. Familiarity with statistical analyses and data integration across multiple sources. Collaborative skills and ability to demonstrate commitment in teams Motivation to pursue a scientific
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production in the making of existential risk imaginaries. To this end, the postdoc will map relevant institutions and actors involved in the construction of existential risk scenarios and inquire the methods
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domain as documented by a PhD dissertation and/or research publications A solid theoretical and analytical understanding of text culture, AI, and related fields Experience of empirical research methods