31 big-data Fellowship research jobs at Nanyang Technological University in Singapore
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physics Demonstrated experience in computer sciences Demonstrated experience in handling large size database Knowledgeable in theoretical physics, and at minima basic knowledge in theoretical plasma physics
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an emphasis on technology, data science and the humanities. We are seeking a highly motivated individual with a strong interest in cancer genetics and genomic medicine to join our research team under Associate
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robotics that works in the small scale and delivers large motion and deformation as the final goal. Key Responsibilities: The Research Fellow will work on a cross-disciplinary project at the intersection
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Requirements: PhD degree in physics Demonstrated experience in computer sciences Demonstrated experience in handling large size database Knowledgeable in theoretical physics, and at minima basic knowledge in
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the SG100K team to shortlist participants for recruitment Run focus groups to get user feedback on procedures and concerns Check data flows, analyze the data to inform future large-scale implementation Write
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, side-averaging, and GLIM. These tools provide new opportunities to explore the Golgi from previously inaccessible angles. Using them, we have gathered preliminary data suggesting dynamic changes in Golgi
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
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an emphasis on technology, data science and the humanities. We are looking for a Research Fellow to conduct AI for medicine research. The role will focus on developing foundation models to medical image
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an emphasis on technology, data science and the humanities. LKCMedicine is searching for a Research Associate/Fellow in the field of Learning Analytics (LA) / Machine Learning (ML) under Professor Andy Khong