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on the resulting algorithms and pipelines. As an emerging paradigm, differentiable programming builds upon several areas of computer science and applied mathematics, including automatic differentiation, graphical
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researchers that conduct their work in the context of multiple European funded projects (RISK-HUNT3R, VHP4S, KWF, EFSA TD-TRAQ, EFSA TXG-MAP), where successful interactions between academia, industry and
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subpopulations, as well as (plastic) cancer cell states that contribute to tumor progression, metastasis, and therapy resistance. The role has multiple responsibilities: ~30% of the time will be dedicated
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to derive overarching scaling principles that apply across multiple disciplines, including hydrology, socioeconomics, toxicology and ecology. To achieve this, you will collect data from databases, reviews
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genuine interest in both fundamental and applied research. The ideal candidate is flexible, self-motivated, and has a collaborative mindset. You will be closely working with experts across multiple
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consolidation work flows; analyse and scale carbon dioxide and methane flux data from multiple locations and transects in relation to explanatory variables from vegetation and soil characteristics, land and water
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the cancer more effectively. In multiple studies, this therapy has demonstrated impressive results after only 4 to 6 weeks of treatment, leading to improved patient survival without recurrence of the cancer
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. Explore options for high level assessment of environmental and social impacts of individual CCUS projects. Conduct multiple CCUS exemplary case studies in the Netherlands and support project partners in
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profile, experience and research proposal. Planning and autonomy: The objective is to study the state of the art of planning algorithms that would support onboard autonomous operations of a rover system on
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going to do Analyze a uniquely extensive neuroimaging dataset (90 minutes of functional MRI per participant across multiple sessions and conditions, detailed structural and diffusion-weighted data