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processes. We then used these models as “digital twins,” testing whether specific types instructional interventions can enhance knowledge acquisition for the model. A human experiment showed that
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species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large datasets that include over 110,000 tree
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models to diverse energy systems and research questions. The ESA group is headed by Prof. Dr. Russell McKenna and generally focuses on the optimization and assessment of complex systems and infrastructures
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of machine learning and high-performance computing, tackling complex, open-ended challenges to deliver scalable solutions. You will design and optimize a software-defined infrastructure that enables cutting
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research questions. The ESA group is headed by Prof. Dr. Russell McKenna and generally focuses on the optimization and assessment of complex systems and infrastructures with an emphasis on environmentally
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molecular biology, microbiology, and cell biology. Job description Design, implement, optimize, and maintain automated laboratory workflows for life science applications Provide expert support for laboratory
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computationally and developing scientific software. Experience in Python is highly recommended, additional knowledge of performance-oriented modeling frameworks, either based on Python (e.g., JAX, Pytorch) or other
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limiting factor to further enhance or optimize viral tropism. In this collaborative project, we explore new ways to adjust this equilibrium so the on/off rates of viral vectors brought in proximity to target