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, where models learn to restore images using only the noisy data itself — without requiring clean references. Existing approaches often rely on convolutional neural networks (CNNs), which identify local
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for practical impact by taking the outputs from the developed machine learning models all the way to the materials discovery lab. From the machine learning perspective, your research will be in the area of
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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if you have worked with prediction models, machine learning or AI models and are familiar with blood cells such as neutrophils, leukocytes and platelets. Work experience in the area is meritorious. If you
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: Verifiable training and trustworthy AI pipelines. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and
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. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and machine unlearning. Machine unlearning
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. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science, or possibly design or cognitive science as main subject) and one at Tema Technology
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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-level courses. Alternatively, you have gained essentially corresponding knowledge in another way. 120 credits (ECTS), or the equivalent, of your total credits must be in a subject of central importance
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will also include teaching or other departmental duties, up to a maximum of 20% of full-time. Your qualifications You have graduated at Master’s level in a subject of central relevance to the field