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Expert in advanced machine learning such as multi-agent generative AI, LLMs, Diffusion models, and traditional machine learning techniques Expert in CALPHAD-based ICME techniques Expert in combining
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, or mental health provision are expected to be higher or lower. The agent based modelling will form an innovation where we attempt to create business models and descriptions of best practices for social
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particularly the CAND multiscale drug discovery platform developed by the Division of Bioinformatics at the University at Buffalo: Integrating the CANDO drug discovery platform with LLM-based reasoning models
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foundation in at least a few of the following areas: high-mobility materials based printed electronics, transient electronics (various sensors, circuits, energy devices etc.), degradable materials, micro
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methods, technologies, and materials to reduce reliance on unsustainable practices and fossil fuel-based compounds as a response to societal requests for green alternatives that maintain high performance
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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agents, with the goal of uncovering novel mechanisms that influence disease progression and potential therapeutic targets. The postdoctoral researcher will contribute to ongoing studies that examine how
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context of defining novel therapeutic agents in Hematological Research. Key Responsibilities: This position is expected to work independently under the guidance of the principal investigator. Projects will
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based on optical trapping or fluorescence microscopy to study RNA polymerase and its response to DNA damage-induced transcription stress; • develop an interdisciplinary skillset by acquiring a
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well as high-throughput screening strategies to identify small molecular compounds that might serve as novel therapeutic agents in disease using cell culture, kidney organoid, and mouse models. Successful