69 algorithm-"Multiple"-"U"-"Prof"-"Simons-Foundation"-"University-of-Wisconsin-Madison" positions in Sweden
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industrial partners and is partly externally funded by the KK Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools
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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
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the autumn of 2025 or as agreed. Project description This doctoral position has a special focus on sustainable data cultures, algorithmic decision-making and AI solutions within municipal companies
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one of the main bioinformatic sites at Umeå university with over 20 bioinformaticians supporting multiple research fields, hosted at the Department of Plant Physiology. The workplace is located right
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research in system and circuit design for next generation wideband radio frontends. The position allows access to fabrication in multiple semiconductor technologies provided by international partners inside
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responsibilities Financial coordination of projects within SciLifeLab in collaboration with multiple universities. Manage budgets, fund allocations, and payment flows Serve as financial contact point for project
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collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
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sites at Umeå university with over 20 bioinformaticians supporting multiple research fields, hosted at the Department of Plant Physiology. The workplace is located right at the Chemical-Biological Centre
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that may remove such constraints, leading to a fundamental challenge: the potential co-existence of genetically distinct clones, each supporting multiple stable cancer cell states. To understand the effect
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering