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methodologies Experience with machine learning techniques Experience with pipeline development and testing (gitlab, simulated light curves…) Ability to work independently and to collaborate in an international
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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-machine teaming. Moreover, the consequences of such digital transformation are explored in the context of workforce and labor developments, organisational innovation, and learning/education. About the
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or an equivalent qualification. For all posts, applicants should also: (a) have solid experience in electric machines, finite element methods and theory of electromagnetic files; and (b) be able to complete
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the research project - “Advancing generative AI algorithms for haptic rendering: bridging human-computer and human-robot interactions”. Qualifications Applicants should have a doctoral degree or an equivalent
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. Preference will be given to those with a relevant portfolio related to system development, human-computer interaction or cultural studies, and/or with knowledge of Cantonese. Applicants are invited to contact
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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exam before 15.06.2026. It is a condition of employment that the master's degree has been awarded. Background in optimization is required. Experience in machine learning is an advantage. Familiarity with
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transformations. Combining automated reaction discovery simulations, microkinetic modelling, machine learning, and global optimization, this project will develop a new and exciting route to addressing one