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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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the Institute of Psychiatry, Psychology, and Neuroscience (IoPPN) in KCL. The candidate is required to: Have a PhD in Signal Processing, Machine Learning, or Bioengineering from a reputed university. Have a
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open PhD positions throughout the year. Learn more about PhD opportunities at the Hertie School and the relevant application deadlines here . Further information on the application procedure can be found
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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methods at the intersection of statistics and machine learning. Collaboration, both within the Department and across the university, is a core value of the Department and a hallmark of the research work
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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