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. This collaboration between Cranfield University and Magdrive will study plume effects of Magdrive's dynamic pulsed plasma thruster on relevant targets. Simulation of plasma expansion and condensation in the space
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requires a dedicated individual with extensive previous research experience, in murine transgenic models and hematology. We are looking for a talented individual to carry out exciting studies in
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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will contribute to the field by: Developing a conversational AI interviewer capable of conducting real-time adaptive interviews. Building an automated candidate ranking model based on interview
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process conditions. Furthermore, this research will focus on the development of a model, allowing for virtual testing and optimisation of the chemical recycling process. This includes potential
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for household who stay indoors, and to prepare for emergency responses. Possible quantitative methodologies include concurrent time-series analysis of outdoor and indoor environment data, prediction model
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xenograft (PDX) models. To this end, the candidate will have direct access to cutting-edge mass spectrometry and advanced bioinformatics infrastructure. The project is part of the collaborative research
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techniques, theoretical modelling, and precise synthetic control – have significantly improved the activity, selectivity, and stability of CO₂-to-alcohol conversion. Key catalyst systems include Cu-based
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leader will be the Head of Department. About the project Modern control systems rely on being at least partially predictive while digital twins also must maintain a state model of the targeted cyber
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to support condition-based predictive maintenance for gas turbine engines. Cranfield has developed unique physics-based technologies on gas turbine performance simulations, diagnostics, prognostics and lifing