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science, computational biology, engineering, statistics, mathematics.). Experience and interest in prediction modelling Proficient in statistical software and programming languages and familiarity with relevant libraries
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postdoctoral experience in the areas of energy flexibility, grid digitalisation, data-driven modelling, and privacy-preserving methods, with a strong publication record. They will have experience of working in
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applies AI to tackle challenges in aquaculture and drug delivery, working at the interface of materials science, biology, and computational modeling. Key Responsibilities: Lead and execute AI-driven
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R&D projects with good understanding of industrial needs. Strong research and technical expertise in the project domain, including experimental design, modelling methods, prototype system engineering
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trajectories; and the modeling of human developmental defects. We are looking for candidates interested in data-driven modeling of biological systems, especially in the context of behavioral changes during
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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cancer. Work in the lab utilizes both genetically engineered mouse models and in vitro systems. A combination of state-of-the-art surgical, genetic, cellular, biochemical, imaging, and metabolic flux
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control for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine
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formation and morphogenesis; the synthesis and decomposition of developmental trajectories; and the modeling of human developmental defects. We are looking for candidates interested in data-driven modeling
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Stig Brøndbo 22nd October 2025 Languages English English English Faculty of Science and Technology PhD Fellow in Knowledge-Driven Machine Learning Apply for this job See advertisement The position A