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intersection of machine learning and life sciences, developing next-generation models that improve our understanding of human biology and enable more proactive, personalized healthcare. As an Industrial PhD
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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PhD Position in Engineering Materials Project: Development and Characterization of Advanced Sorbents
machine elements. In the undergraduate program, the main two programs focusing on the international profile of the Division of Materials Science are important for the department, namely the EEIGM master's
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machine elements. In the undergraduate program, the main two programs focusing on the international profile of the Division of Materials Science are important for the department, namely the EEIGM master's
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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in English (reading, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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research experience in e-health, digital health or a related field experience of, or a documented interest in, machine learning, AI methods or large language models (LLMs) in clinical or health-related