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relevant research or working experience in LLM/VLM and AI decision-making algorithms for end-to-end autonomous driving will be preferred. Good communications skills and the ability to work independently and
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. Skills: Analytical Thinking, Artificial Intelligence Algorithms, C++ Programming Language, Communication, Data Analysis, Feature Engineering, Git, Independent Problem Solving, JavaScript, Linux
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within the university. Tasks may change over time as communication and engagement avenues evolve, so you are required to stay current on popular technologies, trends, and algorithm patterns. Other
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Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic auditing
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assurance/insurance frameworks, including algorithmic insurance contracts, parametric insurance structures, and data-driven risk quantification methods (e.g., conformal prediction and inverse conformal
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of Vienna). About the position: Lead the research group focusing on hybrid quantum algorithms, quantum neuromorphic computing, and quantum machine learning Build your own team (PhD students, postdocs) 4-year
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that combine parallel architectures (i.e., GPUs or accelerator boards, clusters) and numerical algorithms suited to such architectures with the goal of improving the speed of convergence and the stability
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algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals
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combine rigorous algorithm design with applied experimentation in realistic mobile-network settings, with a strong emphasis on research excellence, publishable outcomes, and practical relevance for 6G
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. Knowledge of machine learning algorithms. Proficiency in Canvas and content organization. Excellent communication skills. Responsible and punctual.