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. The following is considered important in the assessment: that you have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within
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have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within generative artificial intelligence to medical images and
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with research duties exclusively. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral
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compression testing UV–Vis spectroscopy Surface profilometry Optical microscopy Scanning electron microscopy (SEM) Experience using or working with machine learning / AI approaches for materials development
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at developing multi-element alloy (MEA) solutions for future hydrogen storage tanks, focusing on both material properties and manufacturability. The project involves (1) leveraging machine learning and artificial
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8 Oct 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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PDF, Dev of new porous transport layer architectures for Proton Exchange Membrane Water Electrolysis
with graduate students, technical officers, and machine learning scientists to design, evaluate and intelligently optimize PTLs with innovative structures, delivering design guidelines for next
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of Machine Learning techniques. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based
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that combine machine learning and classical methods. Work Plan: -State-of art revier and publication of a review paper -Development of classical approaches -Development of hybrid approaches -Journal publication
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(or equivalent) in Computer Science, Machine Learning, Mathematics, or a related technical field. For Postdoctoral Fellows: A completed PhD in one of the fields mentioned above and a strong publication record