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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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Job Description We are looking for a motivated PhD candidate to explore how fish distribution and habitats are linked across coastal and offshore waters in Denmark. The project focuses on improving
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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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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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of ultra-fast MLIPs to simulate the nanoindentation of cemented carbides, a material of industrial relevance, in agreement with and beyond experimental nanoindentation results. Education PhD in materials
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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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with multiple people working on similar problems with different professional and cultural backgrounds. You are therefore a talented, self-motivated, and team-oriented person who enjoys working
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of Science and Technology (NTNU) offers a joint 3-year PhD fellowship. Novel non-target chemical analyses have recently revealed that groundwater and drinking water are contaminated from PFAS, pesticide and