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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an exciting place to learn and
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, including data analysis and visualisation, machine learning, computational methods, and more. If offered the position, you will participate in the following projects, based on your background and strengths
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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for cell transplantation therapies in animal models of Alzheimer's disease, stroke, and epilepsy. To achieve this goal, the candidate will combine a gene network-based approach with a machine learning model
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opportunities within the company. Responsibilities Develop and implement advanced computational and machine learning strategies, including deep learning, graph-based methods, and probabilistic modeling
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CIC bioGUNE (Asociación Centro de Investigación Cooperativa en Biociencias) | Bilbao, Pais Vasco | Spain | 3 months ago
-based approach with a machine learning model (foundational model) to propose protocols for the sequential induction of transcription factors to generate desired cell subtypes. The selected candidate will
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research questions. Strong quantitative research skills and proficiency in Python or R. Experience with large-scale textual data, natural language processing, machine learning, transformer-based models