28 augmented-workers-using-smart-robats-in-manufacturing-cell PhD positions at University of Cambridge
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from
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. Initial analysis suggests recurrent selection of divergent types in multiple locations. The aim of this role is to complete this analysis and prepare a manuscript for submission for publication
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Cambridge, Cambridgeshire, UK. The key responsibilities and duties are to perform experiments with liquid-fuelled and hydrogen flames, employ laser diagnostics, analyse the results, prepare presentations
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information: katie.seaborn@cst.cam.ac.uk To apply online for this vacancy and to view further information about the role, please click 'Apply' above. Please upload your CV and include a brief statement of
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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level. There is no plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills
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plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills, qualifications and
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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general how your profile fits the position using no more than 1,500 words the contact details of two referees PhD (submitted or near submission at the time of application) in a relevant field, or, for
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation