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variety of conditions that are not optimal growth conditions. The survival data of pathogens under these conditions (growth matrices + sub-optimal growth temperatures + antimicrobial stresses) will also be
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for these polymers and implement computational algorithms to assist their optimization. The RISE Polymer Lab is dedicated to developing the next generation of robust, intelligent, sustainable, and evolving (RISE
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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light/heating modules, and selection and sorting routines. Guided by machine learning, we will perform directed evolution experiments where we optimize the synthetic genome that encodes for a biological
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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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the effectiveness of different grinding energies on phosphate liberation within flotation tailings. Developing an AI-driven intelligent framework to optimize grinding time to enhance phosphate liberation with minimum
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optimization, and covalent drug design. Collaborating with researchers and engineers at the Monash Institute of Pharmaceutical Sciences and QDX Technologies to implement scalable AI–quantum hybrid platforms
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but are not limited to: Conduct literature reviews and identify synthetic pathways for modified nucleic acid bases (DNA and RNA) Optimize synthesis protocols and scale-up procedures for producing
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Discrete Element Method (DEM) models to simulate the charging and formation of multi-component, poly-disperse burden mixtures in the blast furnace. The goal is to optimize burden structure and permeability
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-robot interfaces, optimal control, and Robot Operating System (ROS). TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world