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and physical synthesis techniques, along with advanced structural characterization tools, will be employed to achieve this goal. Your primary responsibilities will include: Synthesizing electrocatalysts
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the monomers are reversible, making these polymer materials adaptive, healable, easy to process and recyclable. In this project, you will explore new types of stimuli-responsive supramolecular polymers
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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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equivalent to a two-year master's degree. Your academic background needs to be relevant to the above-stated project objectives, e.g., civil engineering, mechanical engineering, physics, or applied mathematics
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have: good knowledge of quantum mechanics knowledge of electromagnetism and solid-state physics experience with scientific programming with e.g. Python, Matlab, Julia experience with writing a scientific
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of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical
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and Surface Engineering is multi-disciplinary and covers materials science, chemistry, physics, solid mechanics, and manufacturing technology. Properties and performance are evaluated by mechanical
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-essential components of the problem, thereby reducing the size of the subproblems and accelerating the overall solution process. The second line targets the convergence issues often encountered in column
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level equivalent to a two-year master's degree. The ideal candidate will have a background in photonics and condensed-matter physics. You should have a passion for theoretical and computational physics, a
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery