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part of a larger EU project entitled “FEDORA - Federation of network optimization services, simulation foresights, and data alchemy for adaptable, agile, secure, and resilient multimodal traffic
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this process. To facilitate the removal, we can optimize the surface active chemistry such that the system is more prone to destabilize. When several chemistries are present this becomes very challenging and
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for high-speed, real-time implementation. Designing and optimizing experimental setups to achieve low-noise, high-rate performance. Publishing results in high-impact journals and presenting at international
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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optimization Who we are At the Department of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil, plants, animals, humans, and
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and optimize advanced protocols (e.g., single-cell assays, CRISPR-based screens) Collaborate with an interdisciplinary network of computational biologists, clinicians, and international research
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side, you will investigate and develop data-driven methods for optimal and nonlinear control with a particular focus on dual control and on approaches to measurement scheduling and active sensing
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physicochemical properties of PFAS, thereby supporting environmental risk assessments and optimization of removal technologies. Responsibilities and qualifications The postdoctoral researcher will work on the
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, large datasets, physical modeling, optimization, and safety and security are key factors. Our main showcase is the water sector, where we have designed and built a specialized laboratory focused on
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frameworks to support predictive maintenance assessment of PV plants. Your main responsibilities will include: Developing and optimizing daylight luminescence imaging techniques for field inspection