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information. Experience in continuous variable quantum information processing and entanglement generation is preferred but not required. Experience in programming and data analysis. Ability to work
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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will represent a gradient of Ne. In addition to standard bioinformatics work the project encompasses analysis of demographic history and Ne, estimation of inbreeding and genetic load, and eco
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stronginterest and experience with GIS data and tools for urban mobility with someprogrammingskills of Python/R, JavaScript, database management environments, Geographical AI and machine learning workflows
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algorithms, and the integration of models and algorithms into simulation analysis. As a formal qualification, you must hold a PhD degree (or equivalent) in areas such as chemical engineering, chemistry
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methane concentrations Bioelectrochemical systems Sensitive oxygen measurement methods, including electrochemical microsensors and optodes Transcriptomic sequencing and bioinformatic analysis
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interest in information processing in humans and computers, and a particular focus on the signals they exchange, and the opportunities these signals offer for modelling and engineering of cognitive systems
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communication skills are required for this position. We are seeking a bright and empathic person with a PhD in materials science, materials science in soft and biomaterials, MEMS processes, advanced lithography
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) including advance SAXS data analysis and modelling . The following qualifications are also important: Have a good understanding of advanced physical-chemical analytical techniques Experience with in-house
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, geometry and analysis, with a focus on research at the interface of these areas. About the Positions Successful candidates will join a vibrant and international research environment, collaborating closely