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inclusive work environment, dedicated to continuous professional development and learning. Employee referral eligibility is applicable for this position. Job Requisition ID: 31631 Apply now
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. • Applicants with expertise in interface development, micro/nano fabrication, animal experiments, and artificial intelligence would be preferred. • Strong written and spoken communication skills. • Open to
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“Green AI”. Job Description: Work closely with the Principal Investigator (PI) and interdisciplinary team members to support applied research and development projects at the intersection of data, AI, and
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the nation’s education service. We play a key role in the preparation of teachers and in the provision of teacher professional and school leadership development programmes. We are committed to our vision
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to professional development, a vibrant campus culture, and flexible work policies that support creativity and wellness. Collaborate with internationally renowned faculty and passionate students driving the future
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processes, and leading R&D efforts in material science for application development. Drives the development and implementation of coating techniques. Oversee the transition from experimental designs
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meaningfully to Singapore’s next wave of global deep tech success stories. Key Responsibilities: 1. Programme Operations & Delivery Support the development and execution of detailed operational plans aligned
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, to spearhead and conduct research and development to better enable the future challenges arising from rising ambient heat. We are looking for proactive and enthusiastic candidates to be part of our growing team
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Materials Development for Sustainable Rare Earth Element Recovery Using Electrodialysis (AI-REE) Project Introduction: This project focuses on developing sustainable and cost-effective technologies for rare
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interactions between the eye and the brain and in processes by which light can regulate ocular and neurological functioning and development. The goal of our group is to translate fundamental findings in visual