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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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environmental benefits by the increasing use of recycled asphalt binders in new pavements. Under the guidance of a mentor, the participant will participate in the development and optimization of chemical
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genomic approach to profile enhancer dependencies. Develop and optimize experimental workflows integrating scRNA-seq, scATAC-seq, and other single-cell omics. Interpret high-dimensional data in
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the COVID-19 vaccines) is a highly dynamic and fast moving field. We have developed a generative AI algorithm to optimize the mRNA, and we are looking for an experienced wetlab researcher to test the
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electrolyte and polyanion or oxide-based cathode materials. Project aims to optimize synthesis conditions for scale-up production of solid electrolytes (ceramic and polymer electrolytes) and positive/negative
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Engineering, Materials Science, or a related field. Extensive experience in unit operations and chemical processes. Proven expertise in formulation development and product optimization. Ability to design and
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will develop a novel modelling framework that translates climate signals to support cost-optimal long-term investment decisions, while also considering operational feasibility. The successful candidate
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to optimize soil NOx emissions and to understand the underlying environmental and human factors driving the flux variability. The position will report to Prof. Dien Wu (project lead) and is expected to meet
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trials, analyze data, and publish findings in high-impact journals. The role requires active participation in an interdisciplinary team to evaluate and optimize integrated soil fertility management
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one or more of the following areas: (1) modeling of infectious disease dynamics, (2) statistics, machine learning, and AI, or (3) operations research and optimization. Preference will be given