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This doctoral position is part of GRAIL (“Gamma Radiation from the Atmosphere for Investigation and Learning”), a prestigious Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA-DN): https
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sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the goal of enabling predictive, prescriptive, and pre‑emptive analytics. We work closely with
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Netherlands; participate in project publications, research workshops, and other events; build a network with practitioners; and contribute to the project’s overall communication strategy Present your research at scientific
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universities, research institutions, and museums in a highly collaborative network, supported by the Muoniverse Research School, which coordinates training, exchanges, and career development for PhD students and
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an interdisciplinary and international environment. Candidates should send their applications by April 30th through https://cv.newton-6g.eu/ Incorporations will begin in May 2026. DC1: Data-driven models for CF networks
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Institut de Recherche pour le Développement (IRD) | Montpellier, Languedoc Roussillon | France | 2 days ago
to confirm or challenge the initial findings. He or she will also be expected to test and develop new calibration transfer methods, including neural network approaches, notably in collaboration with
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eNSEMPLE. It is an interdisciplinary project at the interface between Statistical Physics, Data Science, Network Science, Computer Science and Sociology, and will involve collaborations with researchers from
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Technologies (KET's) centre. CEPLANT is also included on Roadmap of Large Research Infrastructures of the Czech Republic. CEPLANT boasts a rich network of cooperating institutions in the world. Cooperation with
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thesis forms part of the Nexus network, which comprises five researchers and three PhD students working on a shared theme: ‘The microbial EXposome and the determinants of persistent infections in humans
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analyse both existing panel data and newly collected survey data (e.g. with multilevel regression and longitudinal panel analysis). We will refine existing network measures to better capture inherited