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assays to be undertaken efficiently within petri dish and micro-titre plate format under fluid walls. The candidate will work with other team members to develop relevant biological workflows and design
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Ultracold Polar Molecules" funded by UK Research and Innovation (UKRI). The research builds upon our expertise in creating ultracold RbCs molecules in the rovibrational ground state and trapping them in
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the control and stability of quantum operations. Using advanced Multiphysics simulation tools, the researcher will create models of the physical and control architecture, enabling the identification of design
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group. The positions are associated with a new five-year Programme Grant on "Quantum Many-Body Physics with Ultracold Polar Molecules" funded by UK Research and Innovation (UKRI). The research builds upon
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Associate (PDRA) in Artificial Intelligence (AI). CDSAI is a new university research and innovation centre launched in 2024, strongly linked to the UK’s defence and security establishment (military
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collaboration with statistical physicists for data analysis and experimental design. The Associate is expected to generate breakthrough ideas in the assigned area of research, as well as to carry out research in
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for the development of the autonomous quantum processing unit (AQPU) as follows: Carry out design, experiments, and/or data analysis on specific research topics that we consider most important for realizing the AQPU
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University fosters an inclusive culture of belonging that promotes equity and celebrates diversity. We value a diverse workforce for the innovation and diversity of thought it brings and welcome applications
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with limited supervision to design and accurately execute experiments to achieve the goals of the project. Applicants will be educated to degree level or have equivalent professional experience in
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, immunology etc) * Prior experience with bacterial pathogens Proven ability to design, implement and analyse experiments Experience with eukaryotic cell culture systems Experience with in vivo infection models