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whom to follow and which content is shown to us. These recommendations are often based on social network analysis algorithms, which are used to compute features for all nodes in a social network based on
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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- Ångström Laboratory Research Field Chemistry » Structural chemistry Chemistry » Computational chemistry Researcher Profile Recognised Researcher (R2) Country Sweden Application Deadline 8 Jan 2026 - 22:59
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. The position is a permanent employment with Ericsson. As an industrial PhD (iPhD) you will be employed by Ericsson while also enrolled in the doctoral programme in Electrical Engineering at Chalmers
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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view of machine learning which clearly integrates the two subject areas within the division
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as
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environment within the government-funded strategic research area in IT and Mobile Communications. Read more: https://elliit.se/ The employment When taking up the post, you will be admitted to the program for
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic