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-informed neural networks (PINNs) for integrating mechanistic constraints into ML frameworks, and creating LLM-based agents to assist with mechanistic model construction and knowledge curation. Track B
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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virulence and host resistance, as well as characterizing microbial biocontrol agents. The successful candidate will employ resistance screening of hosts, transcriptomic and genomic profiling to compare
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/przydatne-dokumenty/ Other working conditions Workplace: Interdisciplinary Centre for Mathematical and Computational Modelling Career opportunities: more information: https://rekrutacja-i-rozwoj.bsp.uw.edu.pl
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 22 days ago
microenvironment, and improves CAR-T cell efficacy in preclinical models. The SPECIFIC AIMS of this project are: 1) to determine the impact of PSGL-1 blockade on the immunophenotype and transcriptional programs
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of cutting-edge AI4EO technologies — spanning application-specific AI models, generative models, foundation models, and autonomous AI agents — with applications ranging from ground-based analytics to onboard
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expertise in AI-based optimization and machine learning applied to biological systems. - Experience with Agent-based modeling, and PK/PD modeling - Experience working with diverse, multidisciplinary research
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Postdoctoral Associate – National Tutoring Observatory Postdoctoral Associate – National Tutoring Observatory Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers
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training an autonomous agent to ‘learn’ a control strategy. This formalism is similar to that of optimal control, with the difference that the agent does not have an explicit model of the dynamics