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-generation combinatorial editing tools and applying them to study genetic interactions. As all our projects integrate high-throughput experiments with computational analyses we are particularly interested in
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optimizing simulation tools such as CalPhad to support experimental findings. Conducting in-depth metallographic analysis and establishing correlations between mechanical properties and microstructural
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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of robotics Solid mathematical foundation paired with practical robotics experience Strong programming skills in (at least one of) Python/C++ Familiarity with robotics frameworks like ROS; optimization-based