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the qualifications 7. Certificate of enrollment in a PhD program Submission of applications: orz0822@imbb.forth.gr Selection process Evaluation procedure Applications will be evaluated by a three-member evaluation
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
of Higher Education and Science. Other important criteria are: The grade point average achieved. Professional qualifications relevant to the PhD project. Previous publications. A curious mind-set with
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9th November 2025 Languages English Norsk Bokmål English English PhD Scholarship - Deep learning for forest point clouds Apply for this job See advertisement Key Information The position is part of
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, to undertake a PhD in the Faculty of Arts are available at arts.monash.edu/graduate-research/application-process . Applicants should ensure they familiarise themselves with these requirements before deciding
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integrate multiple signals during communication (e.g., using insights from psycholinguistics and neuroscience to inform computational models of multimodal language processing- Building AI agents that engage
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accurate information. Machine learning allows for the systematization and processing of this data into new forms of information to support the management of forest resources and ecosystems. The PhD candidate
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frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation
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student will become part of a team at DTU with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs
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classification of EEG and auditory signals. The group of the project is multidisciplinary, with experts in signal processing, machine learning, acoustics and language. The successful applicant will perform