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Field
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structure of these networks shapes response diversity and ecosystem resilience. Using network analysis and community detection methods, the project will identify groups of species based on their
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international, interdisciplinary doctoral network. Excellent written and spoken English and strong scientific writing skills. Experience with bioacoustics, machine learning, ecological network analysis, signal
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modelling, resilience indicators, and equity analysis. A central goal of this recruitment is to strengthen the project’s modelling and implementation capacity while deepening its conceptual grounding. We
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designing and evaluating machine learning models for benchmark grids and, depending on data readiness and project progress, by testing them on a real campus network with high-quality consumption and
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reversible languages, algorithms, and architectures for energy-intensive applications. Read more about the network at https://e-core.nws.cs.unibo.it/ . The position is open for talented candidates
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Your Job You will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15 Ph.D. students at 7 universities, one research center and
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developmental biology Optional previous experience with epigenomic data analysis or gene regulatory network inference Ability to work independently and collaboratively in a multidisciplinary
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background in numerical methods, mathematical modeling, and network simulation or analysis Good understanding of power systems, gas networks, or coupled multi-energy systems Proficient in programming
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experience will strengthen your application: Experience with Python, R, Julia, Java, GIS tools, MATSim, transport simulation, network analysis, or similar tools Experience with mobility data, transport
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Doctoral researcher in Food Materials Science: Aerogels for Oral Lubrication - part of a MSCA Doctoral Network on FAroGels - Food-Grade Aerogels for Sustainable Food Systems Department of Food and