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Field
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implement pioneering agentic AI workflows for autonomous materials characterization. We are building the next generation of AI-powered laboratories, where intelligent agents can formulate hypotheses, run
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agents (BCAs) for the control of plant diseases. We are interested in whether plant pathogens can evolve resistance or tolerance to microbial BCAs and if so, what are the mechanisms behind this? Using
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nanotechnology to map the lymphatic system. The successful applicant will work closely with a team of scientists and engineers to develop, evaluate, and validate PCUS and associated contrast agents in bench-top
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parameter space, and using and/or developing agent-based models for the movement and behavior of fish in rivers. Presenting material at conferences, writing research papers for publication, and/or assisting
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Perturb-seq, with our integrative analyses often employing computational approaches such as agent-based modeling to deconstruct gene-regulatory networks and predict system behaviors. As a postdoctoral
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The Los Angeles Cancer Surveillance Program (LACSP), the State-designated agent to collect population-based cancer incidence data in Los Angeles County, in the department of Population and Public
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: Title of Post: Post Doctoral Researcher (Level 1) AI-Minds Project: Trustworthy AI Large Language Educational Models JOB SYNOPSIS Post Doctoral Researcher to develop agentic LLMs tailored to immersive
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. However, there are many knowledge gaps in relation to the use of microbial biocontrol agents (BCAs) for the control of plant diseases. We are interested in whether plant pathogens can evolve resistance
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agents, which are effective but pose significant environmental concerns due to their high global warming potential and their classification as PFAS, now subject to strict regulations. In this context
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researcher, with strong analytical and computational skills, with knowledge of one or all of the following: Dynamic Transport Modelling Demand Estimation and Forecasting Agent-based Modelling and Simulation