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individual interested in pursuing a PhD focused on exploring the complex relationship between housing renovation, efforts to reduce climate impact through increased repair and reuse, and the development
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for real-time decision-making and optimization under uncertainty. Develop techniques for computationally efficient mixed-integer stochastic optimization. Investigate the interplay between energy consumption
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education . Skills and personal qualities In addition to the aforementioned requirements for the position: A demonstrable computational competence, comfortable with using and developing algorithms, data
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life
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algorithms to detect complex structural variants in humans using long DNA sequencing reads. A structural variant (SV) is a large-scale alteration in the genome that involves rearranged, deleted, or inserted
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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develop innovative remote sensing capabilities to monitor oceans, ice, vegetation, and natural disasters. Be part of a dynamic, international team shaping the future of environmental monitoring! About us At
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development of HCFs requires fundamental understanding of light-guidance principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out