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The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a duration of 3
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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Job Description We seek candidates to join the Algorithms Section. The focus of the call is both to expand at the new Vejle campus and to strengthen the Odense campus. We have several openings, and
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Job Description Are you interested in quantum computing? Do you have a keen interest in developing your skills in developing algorithms and software and build the quantum computing infrastructure in
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Job Description The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a
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Assistant Professor (tenure-track) and Associate Professor (tenured) Positions in Computer Scienc...
of Mathematics and Computer Science (IMADA), and other research sections at the department are Algorithms Computational Science Data Science and Statistics Geometry, Topology and Algebra Learning Experience Design
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing
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organizational research examining how different stakeholders (students, faculty, managers, policymakers) interpret, adopt, resist, or institutionalize GenAI technologies in STEM in higher education. Experience
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. The open positions are attached to three different collaborative projects with related but distinct goals, all making use of our expertise in squeezing-based entangled states of light: ClusterQ (ERC): A
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intelligent control and aerial robotics for navigation in uncertain environment. You will be mainly responsible for implementation of machine-learning algorithms for unmanned aerial vehicles; validation