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Field
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of navigating extremely large compositional spaces while simultaneously optimizing multiple target properties such as optical performance, stability, and sustainability. Who we are looking for We seek a highly
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on the theory of deep learning will investigate questions such as the structure and expressivity of emerging neural architectures relevant to space, such as implicit neural fields, continuous normalising
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Qualifications PhD in Civil Engineering, Mechanical Engineering, Applied Mechanics, Materials Science, Physics, or a closely related field by the start date. Strong background in solid mechanics, structural
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responsibilities The postdoctoral researcher will lead the technical and quantitative core of the project. Responsibilities will include: Developing, implementing, optimizing and troubleshooting immersive behavioral
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, laboratory testing, greenhouse experiments, and agronomic validation. Key Responsibilities Develop and formulate new simple and complex fertilizer products Contribute to the optimization of fertilizer
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that leverage state-of-the-art AI methods (deep learning, generative AI, Bayesian modelling, active learning, etc.) to combine cellular imaging data, chemical compound structure, viral genomes and other omics
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. The position is closely connected to our activities within automated quality assurance and structural health monitoring of wind energy components and your work will contribute to the development of new knowledge
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, …). Some effort may be dedicated to finding a tensor network topology (tensor train, tree tensor network, …) allowing to optimally represent vector fields arising from turbulence simulations. Then, this
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opportunity to actively shape change! You can expect a wide range of opportunities: Meaningful tasks: The position offers a varied and diverse role in an international environment Work-life balance: Optimal
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willingness to expand into population and ecological genomics is essential Structured, analytical thinking and a systematic, careful working method Enthusiasm for interdisciplinary collaboration with