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tools developed in the last decade, and compare the networks and task dynamics for the different conditions [11]. We will moreover consider various agent-based models, developed in statistical physics
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science or systems engineering. Knowledge of AI/ML algorithms, particularly graph neural networks and reinforcement learning, is highly advantageous. A keen interest in distributed computing, IoT architecture, and
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‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to pursue a PhD studying how housing policies impact health
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Museum fuer Naturkunde, Leibniz Institute for Evolution and Biodiversity Science | Berlin, Berlin | Germany | 4 days ago
Framework Programme? Horizon Europe - MSCA Reference Number 14/2026 Is the Job related to staff position within a Research Infrastructure? No Offer Description The Marie Sklodowska-Curie Doctoral Network
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This studentship is fully-funded by the Nuclear Threat Reduction network. The successful applicant will be welcomed into our world-leading research programme investigating key nuclear reactions
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in Process Industries; Net Zero (PINZ’) as the programme of study You will then need to provide the following information in the ‘Further Details’ section: A ‘Personal Statement’ (this is a mandatory
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PhD Studentship available on the RAINZ CDT programme at The University of Manchester. Project Overview Abstract: Offshore wind and marine energy assets operate in harsh, inaccessible environments
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19 Mar 2026 Job Information Organisation/Company IMDEA Networks Institute Department Wireless Networking Group Research Field Computer science » Other Engineering » Electrical engineering
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probabilistic generative models for networks; analyze real network data from different application domains; design efficient algorithmic implementations of the theoretical models. You will be supervised by Dr