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stochastic modeling, Bayesian inference, data fusion and modern machine learning. Its research activities span various application domains such as security, non-destructive testing, infrared imaging and
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD position on Understanding and
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the arts and sciences, business, humanities, education, and health and human services, a specialist degree in instructional technology, and PhD degrees in marine science: coastal and marine systems science
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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machine learning (Dr Iñaki Esnaola, Electrical and Electronic Engineering) and advanced machining research (Dr Javier Dominguez-Caballero, AMRC Machining Group), with direct technical support from
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Graphics: https://www.jku.at/cg Your Qualifications: The successful candidate must hold a Diploma/Master’s degree in a corresponding discipline (computer science, mathematics, engineering or related) or have
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of the Quantum & Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI based solutions for predictive inteligence for MRI scanning. The candidate will
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are looking for The following requirements are mandatory: To qualify as a PhD student, you must have a master's level degree corresponding to at least 240 higher education credits in Electrical Engineering
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. As a hydro-focused center, the WERC conducts vital projects that turn sciences and engineering into actionable solutions. By integrating machine learning, sensing technologies, and predictive modeling
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between