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networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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creating novel solutions to major global challenges. Our community is made up of 12 000 students, 400 professors and close to 4 000 other faculty and staff working on our dynamic campus in Espoo, Greater
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strategies for robust statistical models. The project’s scope will be tailored to the candidate’s expertise, offering opportunities for innovation and impact. The successful applicant will join a dynamic
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and
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, usability, and insight into leakage dynamics across diverse constructions. Research Objectives The project is structured around three synergistic work packages: Descriptive Analytics: You will conduct a
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. This post will involve the use of cutting edge biochemical, proteomic, next generation sequencing and ribosome foot printing technologies. This position is available for an immediate appointment. Candidates
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Build Test Solutions Ltd (BTS). This is a fantastic opportunity to work towards a PhD whilst working with both academia and industry. We are looking for a self-motivated student, with an inquiring mind
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and
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fully funded four-year PhD scholarship is available in CDT of Engineering Hydrogen Net Zero at Cranfield University. The scholarship is sponsored by EPSRC and the industrial partner (Hydrogen Waves Ltd