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research colleagues, and to learn about the larger context of my research and the research project. Offer: The aim of this PhD research is to optimize acoustic metasurfaces of finite size using machine
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for providing support to BUSSW MSW students at CRC. In this capacity, the Director works with students, faculty, and staff to foster a supportive and inclusive learning environment that centers equity and justice
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for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD
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(multiple omics, NGSeq, Neuroimaging, text data) with Machine Learning and AI techniques. He actually leads a group with 4 PhD students (1 ITN PhD student) 3 PostDoc Students, and 3 Research Assistants, with
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for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD
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be a hot bed for top quality research and the playground for commercialization and start-ups. Qualifications A PhD degree in Computer Science/Computer Engineering Possess strong background in
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technologies for prototyping and low volume manufacturing of aluminium products.For aposition as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree. We are looking
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Job Type Staff Job Description What we believe Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived
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/Science or Mathematics or related areas. Experience in development of AI/Machine learning algorithms with proven track record in using machine learning and artificial intelligence software libraries (e.g., Scikit-learn
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processing techniques, supported by artificial intelligence and machine learning algorithms, to streamline the interpretation of spectroscopic data. The research will be carried out in close collaboration