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, this interdisciplinary project will focus on developing robust, practical tools to assess and predict recyclate quality. The work will involve thermal analysis (e.g. DSC, TGA), rheology, mechanical testing, and molecular
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effectively identify potential anomalies during testing. You will explore both self-supervised learning and generative modelling approaches, contributing to the cutting edge of medical AI. You will carry out
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behavioral testing facilities Supervision and training by an experienced and supportive team Structured education within the Neuroscience PhD Program of the Medical University of Vienna, including workshops
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safety. You will work on developing control algorithms all the way to performance assessment in test vehicles. The project combines theoretical aspects of control algorithms, experimental design, and
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for a research assistant (m/f/d) - pay grade 13 TV-L, 65% for a limited period of three years. Your tasks: You will be working on a multidisciplinary project that aims to develop and test an mHealth
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commissioning of a new test stand for investigation of wetting behavior and effects of nuclear inhibition Carrying out parameter studies Comparison of different catalyst and membrane surfaces Determination
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will also examine predictors of therapy drop-out by analysing participant factors such as mood, demographics, confidence, and lack of early change. How to apply Please submit an online application
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(Dr Simon Kondrat at Loughborough University) and X-ray absorption spectroscopy at Diamond Light Source and the University of Leeds, you will make, test, and characterise alkali catalysts. Specially
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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project “Ground Rigid Install Pile Anchor – GRIP Anchor”. The project is being led by Gavin and Doherty Geosolutions (GDG) with the aim of undertaking laboratory testing and numerical modelling of a novel