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Field
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; validating models using existing offshore datasets, lab-scale experiments, and collaborating with ongoing projects; developing optimisation algorithms for ensuring techno-economic feasibility of FPV systems
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work hands-on with clinical data and build robust deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image
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data to design robust, efficient deep learning algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates
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service quality. To address these challenges, advanced methodologies and algorithms are needed to design effective revenue and inventory management strategies for complex stochastic systems. The growing
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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: The use of data science and AI methods and techniques within the security and cyber domain, with special focus on ethics and algorithmic transparency; Human-Technology Interaction: Developing robots
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simulated data and ground-based test datasets. The selected intern will become familiar with the Ariel pipeline’s structure and algorithms and will have the opportunity to directly compare its performance and
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of this project is to develop techniques that will enable gate-based quantum optimization algorithms to tackle realistic (large-scale, mixed-integer, and constrained) instances of stochastic programming problems
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decision support algorithms in clinical practice. Additionally, the project involves collaborations with large industrial partners such as Roche Diagnostics and SISCAPA. Through this collaboration, you will
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ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance