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for research. (Required) Knowledge of medical terminology. (Preferred) Demonstrated computer skills/abilities: excellent word-processing skills (Required) Willingness to learn to support study procedures
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probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM, data-driven sensor fusion) is a plus. Underwater or field robotics experience
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The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en/offerta-formativa/dottorato/2025/computer-science About the
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theory and methods by taking several PhD-level courses (about 36 European credits) in information systems, operations management, econometrics, machine learning, extensive data analytics and qualitative
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economic assessments machine learning or proxy-model based methods field scale simulation geological features geomechanics reactive flow The PhD fellow are not expected to master all these topics. Project
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by integrating petrophysics, rock physics, geophysics, geomechanics and machine learning. A detailed project plan will be developed in collaboration with the successful candidate at the start of PhD
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date. Candidates must be willing to move to Denmark for the duration of the PhD research. Please see the RePIM project website (https://repimnetwork.eu/recruitment/ ) for further information
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
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multidisciplinary team spanning hydrology, machine learning, ecological flows, and water resources management.The selected candidate will join the IberianCAMELS research team as a Predoctoral Researcher, contributing