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Field
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interdisciplinary pipelines to identify effective RNA drugs against human diseases: AI-driven RNA discovery – using AI agents to prioritize the therapeutic potential of human lncRNAs (supported by the NHLBI
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recently developed mathematical theory, linking stochastic, network, and agent-based modelling, describing how this emergent behaviour supports essential maintenance and sharing of contents through
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stochastic, network, and agent-based modelling, describing how this emergent behaviour supports essential maintenance and sharing of contents through the mitochondrial population (PMID 38043948). Already
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of multi-agent systems Control and containment: Developing steering techniques and safety measures to guide model behavior, including red-teaming and methods for intervention, guardrails, and safety
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of multi-agent systems Control and containment: Developing steering techniques and safety measures to guide model behavior, including red-teaming and methods for intervention, guardrails, and safety
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based chatbot to instill lifestyle changes including making meal recommendations with appropriate guardrails in place. Key Responsibilities: Developing LLM agentic framework for detection of food, making
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models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search-based methods to achieve personalised and novel outputs. This position will have a
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. • Familiarity with agent-based and compartmental models for infectious diseases. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience. Applicants
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within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR modelling
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including multiple and embodied AI agents. Countering the current trends of very large models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search