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Biology, Department of Life Sciences, to develop intelligent systems that integrate metabolic modeling, omics analysis, and automated literature mining. About us The Department of Life Sciences conducts
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Description Ice and mixed-phase clouds remain a significant challenge for both observational methods and atmospheric modeling. However, recent advances in both areas offer promising opportunities for progress
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Ice and mixed-phase clouds remain a significant challenge for both observational methods and atmospheric modeling. However, recent advances in both areas offer promising opportunities for progress
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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modelling. At the division of Applied Chemistry , we primarily focus on applied research, that is, research aimed at addressing societal challenges and that is ready for implementation either immediately or
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responses, governance models, and ethical frameworks shaping the integration of AI in higher education. We especially encourage research that combines socio-technical perspectives with quantitative methods
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reasoning, conceptual understanding, and self-regulation in learning. Institutional responses, governance models, and ethical frameworks shaping the integration of AI in higher education. We especially
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in AI and cybersecurity to develop novel solutions to cyber-resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by
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development related to the above areas. Publications in first class journals and highly competitive conferences in areas relevant to the work, i.e. network modelling and protocol emulation in virtualised