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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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federated knowledge graph framework that facilitates the querying, consolidation, analysis, and interpretation of distributed proteomics-focused clinical knowledge graphs. To achieve this, we will employ
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theory, symmetry analysis, and group theory. You will work on developing and applying these ideas to discover new photonic phenomena, implement associated computational tooling, and to find opportunities
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Job Description Are you passionate about chemical theory and computation? Are you interested in the real-time (atto- to picosecond) dynamic changes in molecules when they undergo physical and
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Compute we are seeking two outstanding postdoctoral candidates to work on theory of novel protocols, stronger security proofs, and efficient numerical techniques for semi-device-independent quantum
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powerful ideas and tools at the intersection of topological band theory, symmetry analysis, and photonics. You will work on developing and applying these ideas to discover new topological phenomena, design
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such as CO2 absorption in capture solvents and you have a solid foundation in the relevant theory – mass transfer, kinetics, thermodynamics, absorption column modelling. Ideally you have experience with
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tools will be a strong advantage but is not a strict requirement. We expect you to bring an interest in control theory, building energy systems and modelling, and to enjoy working with both theory and
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. The ambition is to develop lab exercises that directly support and illustrate the abstract mathematical theory of the subjects, and to measure whether such exercises improve the learning process. You will be