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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
such as on-chip optical routing, flexible optoelectronics, light emission, optical sensing and quantum communications. This is an ambitious research program, with a strong interdisciplinary nature, across
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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, including dealing with problems that may affect the achievement of research objectives and deadlines. • Contribute to the planning and organising of the ReLiB research programme. • Co-ordinate own work
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We are recruiting a Senior Research Fellow in Infectious Disease Modelling to join a collaborative research programme in partnership with the Modelling and Simulation Hub Africa (MASHA
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of an ageing population. The postholder will support the programme through the application of a range of techniques and/or to collect and analyse data that enable the project to progress. This position involves
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have a positive attitude. Working with academics, researchers and PhD students in managing and conducting research activities across the programme, you should have experience of working collaboratively
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academics, researchers and PhD students in managing and conducting research activities across the programme, you should have experience of working collaboratively on projects with a wide range of stakeholders
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academic and volcano monitoring agency Project Partners in Chile and Argentina, along with the entire project team. You will plan and conduct two field campaigns to Diamante-Maipo to map, log and sample its
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Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within the research programme of the Elementary Particle Physics Group. To work on detector
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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis