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, application of machine learning methods to climate science. Climate models of varying complexities and their possible mitigation strategies. Emergence of extreme events in weather and climate. Research
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to teach basic courses in AI (in particular machine learning) for non‐technical audiences, and advanced courses for expert and professional audiences, in particular on generative AI methods, while developing
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methods, including the development of organocatalytic asymmetric transformations and the development of small organic molecule catalysts used for asymmetric transformations 2. Development of protein
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qualitative research methods. Applications will be considered on a rolling basis. Please submit: A cover letter including teaching interests. Your curriculum vitae (CV). One writing sample. (Optional) A
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of applicant to the publication, number of citations, impact factor of the journal), h-index, monographs, participation in international conferences (outlining the invited lectures), patents, projects
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, (6) Metal and inorganic materials, (7) Organic materials, (8) Biomaterials, (9) Data-driven materials development, and (10) Advanced materials analysis technology. Internationally highly esteemed
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: (1) hydrogen-related materials, (2) battery materials, (3) quantum materials, (4) semiconducting materials, (5) artificial intelligence materials, (6) metal and inorganic materials, (7) organic
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teaching and research at a reputable institution. Key Responsibilities: Teaching: Develop and deliver undergraduate and/or graduate courses in specific subjects or fields. Utilize innovative teaching methods
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) Artificial intelligence materials, (6) Metal and inorganic materials, (7) Organic materials, (8) Biomaterials, (9) Data-driven materials development, and (10) Advanced materials analysis technology. Highly
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. To achieve such an ambitious goal, the candidates are expected to bring us with new ideas, new technological advance and highly skilled in experimental methods. More details about our laboratory can be found