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Field
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of biological systems. Familiarity with AI techniques, such as physics-informed neural networks (PINNs), is preferred but not essential. Experience with high-dimensional data analysis (e.g., transcriptomics
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preparation of scientific publications related to the project. The postdoc will work in close collaboration with a network of bioinformaticians specializing in the design and development of data analysis
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theme is the role of geodetic expertise in designing and evaluating IS-InSAR networks after data acquisition, analogous to optimal network design in conventional geodesy. Job requirements The successful
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). At all scales, faults form dense networks (aka fault zones) including a master fault and myriads of secondary fractures and faults that intensely dissect the host rock. Whether it is a master or a
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technologies, as is proficiency in advanced statistical analysis- particularly in R or similar- for interpreting large environmental datasets. Ideal candidates will have a robust publication record, experience
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of strategies to reduce mobile network energy consumption, with a strong focus on the RAN and clear service-quality constraints • Leveraging Network Digital Twinning and what-if analysis frameworks
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postdoc to study how supply chains can stay resilient and meet regulatory demands, using system modeling and scenario analysis. Job description Supply chains are increasingly exposed to complex and
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the impacts of rapid and longer term spatial agricultural shifts, due to international trade networks, on biodiversity, considering losses and gains and how this can be used to allow more direct comparison of
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that connect economic systems, energy transitions, climate impacts, and air pollution to support policy-relevant analysis. The group integrates insights from climate science, atmospheric/aerosol research, and
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic