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that have demonstrated experience imaging, engineering and at least some understanding of cardiac electrophysiology. Recent PhD graduates (or equivalents) with training in any field of biology are welcome
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interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD in one of the following: Data Science, Computer Science, Computational Social Science, Information
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on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in graph-based prediction. What we’re looking for: A PhD in Electrical and Computer Engineering or a
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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: extremal graph theory, Ramsey theory, probabilistic combinatorics. • Candidates should have (or be near completion of) a PhD in mathematics. • Candidates should have a strong research record in Combinatorics
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inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science
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—we do not work from home. Candidate Candidates will have completed a PhD in theoretical physics or mathematics. They will have strong analytic skills, meaning they are adept at solving equations, and
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look forward to receiving your application! For more information regarding the employment https://liu.se/en/work-at-liu/vacancies/27309 Your work assignments The PhD position is part of
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opportunity to design and implement novel digital technologies in collaboration with a wide range of academic collaborators. You will be part of a larger team of Research Associates, PhD students, and a
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relevant expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph