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cues play a role analogous to conditioned stimuli: they are signals that, once learned, allow the agent to anticipate the consequences of its actions. Scientific Motivation: Learning-based navigation
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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cyber resilient AI, promoting education, knowledge sharing, and policy development. This PhD position is associated with the research theme Runtime Security Assurance. Once trained, AI models can be
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-based modelling). Flexibility to travel and engage fully in academic and non-academic secondments abroad Specific Requirements As per the specific eligibility criteria of Marie Sklodowska-Curie Actions
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks
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Scholar (FP01) – AI Imaging & Retinal Disease who is interested in ophthalmology to assist in refinement of AI models as well as validation of new biomarkers and data analysis to be able to predict whether
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Japan and North America, to improve an existing model for the spread of Cyvirus cyprinidallo3 (also known as Cyprinid Herpes Virus or CyHV-3) as a biocontrol agent for common carp in Australia
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theory. Proficiency in Python for rapid prototyping, data analysis, and potentially using libraries for network science (NetworkX) or agent-based modelling. Flexibility to travel and engage fully in
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related fields to apply for this exciting opportunity in the Brown Group in collaboration with EDF UK to develop skills in agent based modelling spatial-analysis, optimisation and economic analysis, as
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and responsibilities The Project Expert performing as Senior AI Solutions Developerwill: Develop and implement advanced AI models, including deep neural networks, transformers, LLM-based systems