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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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modelling, agentic AI, uncertainty estimation), and an interest in clinically-grounded oncology research. We particularly encourage applications from individuals across all groups traditionally
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for extension. We are looking for someone to join our team of consumer behaviour scientists and agent-based modellers who can bring knowledge of and experience with modelling cognitive or behavioural change
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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model integrity and data confidentiality. The successful candidate will develop novel frameworks that enable effective collaboration among language model-based agents without exposing proprietary
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experience in several of the following topics (ordered by importance): Large language models and LLM-based agents Human-AI interaction, human-computer interaction and human factors Reinforcement learning and
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engineering discipline. Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics (ordered by importance): Large language models and LLM-based agents Multi
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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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interests in biomedical NLP and medical LLMs, multimodal and foundation models, ophthalmology and medical imaging AI, and real-world applications in biomedicine and healthcare. Please visit https