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group have developed an AI-enabled system which can extract detailed retinal vasculometry characteristics from colour fundus photographs (CFPs) in a fully automated way, allowing application to large
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for sustainable production of food by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to do exactly that in a dynamic research environment. In the SOLARSPOON
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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Are you interested in developing computational tools to understand the detailed mechanical behaviour of multi-phase materials? Then this PhD position at Chalmers University of Technology might be
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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pa Fixed term Ref: 095093 You will join the group of Professor Alessandro Troisi based in the Materials Innovation Factory (https://www.liverpool.ac.uk/materials-innovation-factory/ ) to work on a
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computational mechanics of composite materials, and should be enthusiastic to work in a collaborative project between industry and academia.Vacancy 3: PhD (4 years) or postdoc (3 years) on mechanical modelling
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Materials Science and Engineering (PhD programme in Materials Science and Engineering - NTNU ) within three months of your employment contract start date, and that you participate in an organized doctoral
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expertise and facilities in electrochemistry, materials chemistry, advanced characterisation techniques (including a variety of spectroscopy, microscopy,) modelling and battery and fuel cell construction and