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optimization and Al tools to coordinate and optimize the role of ESS within the onboard microgrid. This project finds it context in the urgent need to reduce greenhouse gas émissions and improve the energy
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will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell lines). Designing, establishing protocols and conducting recombinant
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, CT, and other imaging techniques. Design and optimize multiparametric models to analyze complex imaging datasets and extract clinically relevant features. Develop and optimize newer clinically relevant
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from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular
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theoretical basis for modelling functional biodiversity, based on eco-evolutionary optimality (EEO) theory. The PDRA will be explicitly responsible for statistical analysis of plant trait data and the
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proteins. Under the supervision of the project leader, your responsibilities will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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an integrated model of plant carbon allocation, based on eco-evolutionary optimality theory. The PDRA will be explicitly responsible for designing an approach to evaluate and model carbon allocation to non
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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system optimization for remote construction. This position will focus on advancing research in construction assembly science and technology, logistics optimization, and real-time communication frameworks