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medicine research team and key academics and investigators across the rheumatology and cardio-rheumatology field and imaging groups to support novel and ambitious research studies. The post requires working
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. The position is placed in the Digital Signal Processing and Image Analysis group (DSB), Section for Machine Learning, Department of Informatics at the University of Oslo. The DSB research group has seven full
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Submission Candidates must access and register on the electronic platform https://apply.uc.pt/ to submit their application, selecting the procedure to which they wish to apply. Documents uploaded
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imaging. Key Responsibilities: Design and carry out ultrasonic experiments and develop signal processing techniques Develop theories of acoustic wave propagation in complex materials Design numerical
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 9 days ago
will be undertaking research for the observational seismology program at RSES with a focus on data acquisition for Earth Imaging. Candidates who have previous experience with numerical seismology, data
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dementia, driving a step change in our understanding of neurodegeneration, and accelerating the discovery, development and delivery of interventions that will help diagnose, treat, and ultimately prevent
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, works on genetic and environmental factors shaping the human brain across the lifespan. Ultimately, we wish to identify key processes necessary for building resilience to brain disease. We use a
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Posting Summary Logo Posting Number RTF00030PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Postdoctoral
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20 Feb 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
resolution mammography images. The model should be trained using a combination of weakly supervised learning, for images without local annotations, and fully supervised learning, for images with corresponding