5,379 machine-learning-"https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" Postdoctoral positions
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Metabolism Postdoc Appointment Term: 2 years Appointment Start Date: Rolling admission, applicants can apply as soon as possible. Group or Departmental Website: https://www.research.va.gov/programs/bd-step
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of these heat waves. Collaborate with interdisciplinary teams to address complex research questions and solve real-world problems. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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the oxidation state and the electric-polarization direction in HfO2. Project included in the activities of the MEM group of CEMES, funded by the labex NanoX. Where to apply Website https
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Experience as a member of a research project team Knowledge of Romanian and English Research FieldPsychological sciencesYears of Research Experience4 - 10 Additional Information Selection process https
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separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
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, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports departments in integrating active
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. What We Offer As an employer, we
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, data driven, computational, and intelligent systems, all with a strong interactive component. The Digital Interactions Lab (DILAB) is a small but vibrant human-computer interaction research group within
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broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict