85 parallel-processing Fellowship research jobs at National University of Singapore in Singapore
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Institutional Review Board (IRB) requirements. Oversee project teams, staff allocation, budgeting and procurement processes to support programme productivity and continuity. Prepare and coordinate reports
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addition to annual leave, the Research Fellow may apply for leave to undertake research and fieldwork overseas, subject to the approval of the CIL Director. Application Procedure Application should be submitted online
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aspects of computational modelling, brain-computer interface technologies as well as within NUS focusing on design and application from the lens of landscape architecture. Key Responsibilities: Assist
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, Immunostaining Assisting and handling mice work such as animal husbandry, live ophthalmic imaging, dissection, and processing of mice eye tissues Contributing to the writing and presentation of project updates
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optimizing fabrication and testing processes for new devices. Qualifications PhD degree in Electrical Engineering, Materials Science, Mechanical Engineering, Biomedical Engineering, or a related field with
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. • Excellent research support provided by the School and NUS. Application Procedure: Interested applicants are invited to send the following list of documents via the NUS Career Portal. • Cover letter
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. Qualifications Experience writing/using computer code Experience supervising postgraduate students and/or staff Experience presenting research findings at national and international conferences, seminars, and
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. Qualifications Experience writing/using computer code Experience supervising postgraduate students and/or staff Experience presenting research findings at national and international conferences, seminars, and
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(CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum
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. ● Computational skills is a plus (e.g., experience with computational modeling, AI models, familiarity with Python, etc) ● Familiarity with EEG, Brain-Computer Interfaces, biofeedback systems, or biomarkers