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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Umeå Institute of Design is
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. Conducting most of the development in a digital environment is particularly important when dealing with mobile, heavy and powerful machines, and especially in the early development phases when they exist only
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
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development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The position is aimed at researchers early in their career
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research at the department, such as: real-time and embedded systems distributed systems security and privacy formal methods artificial intelligence and machine learning Pedagogical expertise The pedagogical
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advising on methods and systems, assessing quality and properties of data, assisting with resource allocation proposals, machine learning workflows, dataset curation, organization, and sharing, data
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learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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or explainable AI or safety). Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models. Experience in analyzing multimodal data (e.g., text, sensor
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. Use advanced data processing services to perform bioinformatic analysis. Apply machine learning methods to complex sequencing and protein structure data. Qualifications You should have a minimum a high