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Field
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of the call Past experience in AI algorithms Past experience in Research Projects EVALUATION CRITERIA The selection will be based on the following criteria: Academic record (50%) Past Experience in AI
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: include developing reconstruction algorithms for the muon bundles recorded by KM3NeT; extracting air-shower observables such as muon multiplicity, lateral separation and energy; using these observables
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units and sensors. A project environment well suited to students interested in careers in academia, advanced R&D, or industry innovation. What you should have We are seeking a motivated candidate with the
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with advanced photoreactors, modular LED light sources, inline analytics, and machine-learning algorithms for the autonomous optimization of photocatalytic reactions. Research will address key challenges
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mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering, or neural networks). Non-negative tensor factorization
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subject from a recognised institution. A background in at least one of the following: Dynamical systems Photonics/Electromagnetics theory, design and simulations Machine learning mathematics and algorithms
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, PyTorch), Machine-learning mathematics and algorithms. Experience in Imaging systems (e.g. microscopy), and optical laboratory experiments (lasers/lenses) Funding and eligibility Open to UK, EU and
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explore applications of quantum resources in a network setting. Among the research topics are quantum cryptographic algorithms and quantum error-correction. How to apply Your application must include
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, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms, memory technologies, and neuromorphic hardware architectures for future
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without invasive surgery. Project background We develop advanced focused ultrasound technologies, adaptive closed-loop control algorithms, and ultrasound-responsive micro/nano therapeutic carriers as an