83 computational-material-science-"Multiple"-"Humboldt-Stiftung-Foundation" PhD scholarships
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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Graduiertenzentrum Gesellschaftswissenschaften (KIGG) The Inter-University Doctoral Programme in Economics (MAGKS) Circular economy of urban carbon flows through innovative bio-waste recovery pathways (CirCles
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project description: Inkjet printing allows multiple materials to be 3D-printed simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage
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profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials chemistry, theoretical chemistry, molecular
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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will, in addition, sharpen your didactics skills through experience as a teaching assistant. You must hold a two-year master's degree (120 ECTS points) in Robotics, Electrical Engineering, Computer Science
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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