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Field
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moral cognition, and AI safety. Human societies have solved an extraordinary version of the multi-agent alignment problem, getting millions to billions of individuals to cooperate, coordinate, and enforce
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what alignment is required between the world models of agents and humans that collaborate. You also develop communicative strategies for the agent to detect misalignments and take actions to resolve
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based on an individual-centered spatial analysis approach (geomatics) using AgentBased Modeling to model mobility and its evolution. The postdoctoral researcher will intervene in the second phase
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work with microbes, in vitro cell cultures, and human biofluids such as serum. We have a strong focus on mass spectrometry-based proteomics, which we routinely integrate with genomics data and phenotypic
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optimization and LLM alignment: design preference-based training and fine-tuning methods (RLHF, PPO, DPO, reward modeling) for medical and multilingual LLMs. Agentic and tool-augmented AI systems: develop
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, or trustworthy AI agentic AI, multiagent systems, sequential decision making, and LLM-based reasoning embodied or physical AI, robotics, autonomous systems, or intelligent infrastructure systems strong programming
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frameworks using reducing agents under inert conditions • In-depth analysis and characterization of CO₂ chemisorption in modified covalent organic frameworks • Preparation of electrode materials
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compositions of these materials with potential adsorption properties for simulants of toxic agents or catalytic properties of interest for degradation action, a molecular modeling approach based on density
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learning and LLM frameworks like LangChain and agent-based LLM frameworks, Retrieval Augmented Generation (RAG). Experience with fine-tuning, deploying, and evaluating Large Language Models. Experience with
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online support platforms (e.g., 7Cups), we are developing prototypes that use LLM and conversational agents to deliver scalable, experiential micro-skills training (such as empathy, active listening, and