150 algorithm-development-"Multiple"-"Prof"-"Prof"-"SUNY"-"St" positions at University of Manchester
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Overall Purpose of the Job: To provide clerical and administrative support for the Centres for Doctoral Training (CDTs) in Developing National Capability in Materials 4.0 and 2D Materials
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counterparts, encompassing joint research, knowledge transfer and exchange of best practices. Research in TAICHIP consists of developing advanced design methodologies for energy-efficient and reliable AI chips
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processes to performance to underpin development of wasteforms specifications, working closely with partners at University of Sheffield on other ceramic wasteform candidates. You will also be a key member of
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Accountabilities Leading the development and delivery of a University-wide public affairs strategy and influencing map Promoting research outputs and expertise to influence public policy and decision-making Building
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This post is based within the Research Degrees and Researcher Development Team (RDRD) within the Directorate of Research and Business Engagement (RBE), which supports the ongoing development of strategy and
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responsible for managing and optimising how CRM platforms are used within the University. We are responsible for the development and maintenance of several Microsoft Dynamics 365 implementations that support
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focus on digital manufacturing, artificial intelligence and machine learning. You will join a dynamic research environment at an exciting time to further develop the Department’s research profile. You
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We are seeking a motivated laboratory-based Research Technician to join a dynamic lab working to understand the evolution of antimicrobial resistance within human fungal pathogens. This role is
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assisting the Directorate and its senior leadership team in achieving organisational goals efficiently. Key Responsibilities: Reporting directly to the Chief Property Officer, you will: Lead the development
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a central role in the development and adaptation of the next generation of biomedical foundation models, large-scale, domain-aware LLMs capable of reasoning across biomedical literature, clinical