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complex metal structures. This opportunity is centred around improving manufacturing productivity with advanced laser-matter interactions control and optimisation. The PhD will advance our comprehension
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structural alloys. The project will combine advanced phase-field fracture mechanics, continuum-scale chemo-thermo-mechanical modeling, and advanced machine learning techniques for enhanced prediction accuracy
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plus Familiarity with FE simulation tools such as ANSYS or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience
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or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience with coding, ideally in Python or MATLAB Funding support This
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mechanical and chemical properties; fully 3D-printed electronics; and devices with mechanical or electrical responses encoded into their structure. However, we don’t yet know how to design these complex
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integration and plasticity at spinal nociceptive synapses, with particular emphasis on sex-specific mechanisms and glial adaptations that may influence the transition from acute to chronic pain, as well as its
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principles with micromachined mechanical sensors that measure the flow through the bending or displacement of a mechanical structure. In this way, we expect that, in addition to mass flow, many relevant gas
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this position, you are expected to have: A solid foundation in concrete technology, mechanics of materials, and structural engineering A strong interest in experimental research Prior exposure to or interest in
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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
mechanisms underpinning LMTK3's multifaceted role in cancer biology. By employing a multidisciplinary approach combining structural biology, biochemistry, and cell biology, this research aims to provide novel
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure