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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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delivery or regenerative medicine. The student will formulate new 3D-printable materials and develop new design methods, for functional 4D-printed devices with either fast self-resetting responses or complex
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to achieve complex and customisable micro-robots to provide personalised healthcare solutions. Advantages: This studentship will take place in world-leading research laboratories for additive manufacturing
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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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necessary to 3D-print the next generation of medical micro-robots targeting drug delivery, exploiting combinations of functions to achieve complex and customisable micro-robots to provide personalised
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materials and develop new design methods, for functional 4D-printed devices with either fast self-resetting responses or complex multi-scale shape changes, applicable to biomedical, micromechanical
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project aims to address the knowledge gap by investigating: - How ML methods can be adapted for complex, real-world conditions, including noise and interference, - How such methods can be
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“Light- versus electron-induced spin-state switching of complexes on insulating layers” within the Priority Programme SPP 2491 “Interactive Spin-State Switching” This DFG-funded project aims
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Funding: School of Computer Science studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email
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Engineering Risk and Complexity (MERC) Program duration: 4 years No. of scholarships: 5 Coordinator: Prof. Mario di Bernardo Contact e-mail: merc@ssmeridionale.it 9. Molecular Sciences for Earth and Space