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Field
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to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world application. The successful candidate will work at the intersection of multi-disciplinary
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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positively impact the world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach others every day. Visit our
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the emphasis of the position will be on the development of nanomaterials for AM and understanding of AM process optimization, functional materials design and compositional grading, electrochemical and
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, with a focus on arboviral diseases (e.g., dengue or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation
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development of novel traits. The successful candidate will be expected to develop and optimize protocols for various ‘omic techniques (single cell transcriptomics, proteomics, etc.) and other techniques
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smectite, sepiolite, and layered double hydroxide. -Summarize the MD data to find the optimal mineralogy properties need to maximize the binding efficiencies of the minerals for the toxins. -Summarize
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. Experience working with rodent models. Experience with mammalian cell culture. Experience with live-cell or in vivo microscopy. The optimal candidate will have a background in neuroscience or cell biology, as
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nanomaterial-nucleic acid hybrids for optimal device bio- and gas sensing, as well as for optoelectronic applications. About You The candidate will have experience in materials science research and ideally DNA
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and