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candidate will work fulltime on the above-outlined research project. It is expected that they will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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another way. The candidate must possess experience with the following technologies: - CUT&RUN - qRT-PCR and - Extensive DNA cloning technologies - Experience in Codon optimization from Dictyostelium
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contribute to the activities including TES unit development, laboratory testing and techno-economic analysis to identify optimal integration opportunities. Cooperation with industrial and academic national and
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the optimal design of social support systems. The PhD position primarily concerns the part of the program that studies how AI changes the organization of work and employees. The program currently includes 12
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to multiple methods used in financial or actuarial mathematics, such as extreme value theory, inference for stochastic processes, optimization theory, and/or Monte Carlo simulations. Experience in obtaining
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and optimize the detailed methods to pursue the overall project goals and, after a training period, independently analyze genomic data using machine learning and other statistical methods. All work will
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social marketing within technology and innovation-intensive activities to automation and optimization, to machine design, production and production systems. The Division of Industrial Engineering and
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responsibilities of the successful candidate will be: Perform research in designing, synthesizing, and characterizing electrocatalysts for optimized amine-mediated CO₂ reduction. Perform mechanistic studies and
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topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the postdoc can be involved in