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development and engineering work for NLP (Natural Language Processing) products under AI Singapore. To complement the current NLP Hub team, we intend to hire an experienced NLP engineer with expertise in
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office is hosted by the National University of Singapore (NUS) and brings together all Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies developing AI products
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to design and perform experiments for microbial strain engineering, gene expression, protein expression, enzymatic assays, microbial fermentation, and product recovery; Know how to work independently and in a
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specifications, evaluating and recommending potential solutions and vendors, contract management, etc. - Be accountable for the Total cost of Ownership, including both the product license and professional charges
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fermentation, and product recovery; Know how to work independently and in a team, have an investigative nature and a strong attention to detail; Possess an established record of international publications
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a recognised University At least 5 years' progressive career track record in a marketing or communications role Proficient in research, editorial and speech writing, presentation and product packaging
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projects deliveries, application enhancements and operation support that are related to the Faculty Administration business. He/she will also be responsible for product success across the whole product
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excellence. • Provide direction and guidance to teams in managing the full data lifecycle. • Develop and implement strategies to enhance team performance and productivity. • Foster collaboration and high
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production from CO2. The successful candidate(s) will closely collaborate with Prof. Jee Loon Foo, Prof. Julius Fredens, and our research team to advance the frontier of synthetic biology in addressing real
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are at the intersection of economics and computer science. Specifically, the projects on mobile apps use deep learning-based natural language processing models (GPT-4, ROBERTa, etc.) to extract information from textual