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properties are attributed to light capture for photosynthesis and radiative heat dissipation for temperature management, whereas the role of structural leaf surface properties, such as the presence of bumps
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implement an integrated, data-driven digital twin of the national energy system, capable of simulating and analyzing multi-energy infrastructures (electricity, heat, gas, hydrogen) across spatial and temporal
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experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in
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electrical engineering, automation, computer engineering, or a closely related discipline, with proven expertise in the operation and control of intelligent energy systems. Experience and skills Solid
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We have performed such studies
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Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding algorithms, or demonstrated ability and
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compensation is based on multiple variables. This range represents annual salary only and does not include supplemental performance-based pay or any one-time payments that eligible candidates may be offered
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The project will be part of the new DREAM (Dermatology Research Across Multiple Disciplines) Center financed by the LEO Foundation. You will be part of building this new center which spans over Aarhus