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Job Description Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges? Responsibilities and
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limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data. You will work at the frontier of active learning and ML-guided
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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conducting high-quality research at the intersection of thermo-fluids science, AI/machine learning and optimization. We envision that: You have an open mind and can think creatively in engineering
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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms
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methods including machine learning methods to integrate genomics, transcriptomics and epigenomics data set to uncover genomic-epigenomic interactions and cancer evolution trajectories. The tasks will