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for interacting with higher degree by research candidates, staff and industry, together with a strong commitment to teamwork and multidisciplinary collaboration. Values-led approach to academic practice and
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-base and tangible recommendations designed to improve social media data access in the immediate and long-term. Social media data – data generated through user interactions with digital social platforms
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for the research group: • Conduct CCS related experimental studies to obtain rock properties, evaluate rock/fluids interactions, and obtain results to be use in the development of CO2 storage site(s). • Use
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analysis using HPLC, AAA, LC-MS characterization. To carry out structural characterization of alternative proteins and digested peptides using CD and FTIR spectroscopy. To closely interact with our
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University places high value on in-person collaborations and interactions, and we expect selected candidates to participate in-person. Ph.D. is expected. The work location for this position is in-person
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interactions across a range of physical platforms to build large-scale, hybrid quantum networks. Our work spans rare-earth-ion-doped solids, alkali vapours, quantum dots, and nonlinear photonic media, aiming
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positive impact through cross-disciplinary interactions. Actively seeking new funding and creating opportunity for spinouts. Working towards real-world outcomes. Integrating large-scale data, AI, and
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imaginative ideas and approaches. We’re not afraid to do things differently. We are open. We’re highly collaborative and interactive, and make sure our activities are visible to the outside world. We
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interactions, especially those that involve substantial uncertainty and limited attention. We study situations in which people have non-instrumental reasons to care about what they and others believe, as
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willingness to work in a highly interactive and collegial group. The applicant is expected to provide significant input into the development of AI Machine Learing Data Collection databases, procedures and