1,993 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" "Univ" "UNIV" positions in Singapore
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HOP Tool (HOP V1) and preliminary tool completion guide. In Phase 2, HOP V1 will be piloted with K2 educators and will be refined into HOP V2 based on psychometric data and stakeholder feedback. In
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managing the scheduling, data collection and quality assurance of EEG, MEG, fNIRS and fMRI research projects. You will also collaborate with researchers and directors to ensure sound technical support for
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on data collection, data cleaning, data management, and basic statistical analysis using SPSS and/or R, with opportunities to contribute to figure/table generation and external reports and publications
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processes, including application management, interviewing scheduling, and applicant communication. Provide information to prospective students, parents, and schools regarding admissions and financial aid
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and acquire spectral data Perform Raman spectral data analysis using machine learning algorithms Work with DiSTAP plant biology collaborators, training researchers in spectrosocpy Work with local
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to generate and process application data/documents, perform checks and verifications, liaise with donors, faculty and students to arrange interviews and preparing data for selection committee. Ensure awards
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Environmental Engineering | NTU Singapore Key Responsibilites: Rigorous study design. Wet-lab experiments. Perform in-depth, critical data analyses. Effectively communicate through presentations and high-quality
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the mechanisms contributing to sporadic ALS progression, helping to pave the way for novel therapeutic strategies. They will collaborate closely with data scientists and experimental colleagues to ensure thorough
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the Office of Information, Knowledge and Library Services (OIKLS). It is responsible for the provision of seamless access to information resources and library services critical for the NTU community’s teaching
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of our intelligent operations. As an AI & Systems Engineer, you’ll design and scale the systems that power our AI agents and data-driven workflows — from API integration to cloud architecture and data lake