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experience or strong interest in power system modeling, optimization, machine learning, and control systems. Documented programming experience (e.g., GitHub projects) in Python, Julia, MATLAB, or similar
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computer vision, deep learning, and logical reconstruction techniques. The research investigates how multimodal imaging modalities - including scanning electron microscopy (SEM), photon emission microscopy
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outcomes research and real-world data analytics, with a strong publication record. Proficiency in advanced data analytics, machine learning, and statistical modeling. Job Description: The Department
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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that employ novel virtual reality and robot-based paradigms. We are also leveraging several analytical tools such as computational modelling and machine learning. As a Research Assistant, you will help collect
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Responsibilities • Implement and test statistical and computational models for infectious disease dynamics (compartmental models, Bayesian inference, phylogenetic analysis, or machine learning pipelines depending
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invoices, and other administrative duties as needed. Willingness to be trained in murine models of infection, tolerability and pharmacokinetic studies. Assist with the preparation and coordination
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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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field. Strong foundations in machine learning and familiarity with current AI tools and practices. A solid understanding of large language models, in particular their reliability, security, and
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dementias • Glial biology and remyelination, including androgen receptor-mediated repair • Advanced imaging and experimental models, including high-resolution two-photon imaging, mini-2P systems, and