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Field
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numerical simulations with optimization algorithms and software tools. · Carry out experimental validation of simulation results Is Your profile described below? Are you our future colleague? Apply now
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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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and determination? We are currently seeking a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective
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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. Linköping
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PhD Studentship in Computer Science: Quantum-Safe Security for 6G Networks Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £21,805 (2026-27 UKRI rates
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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support massive Internet-of-Things (IoT) deployments through technologies such as network slicing. At the same time, the emergence of large-scale quantum computing poses a significant threat to current
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about AI, multi-modal sensing, and
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agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and behavioral well-being, particularly among vulnerable populations. Applicants are encouraged to approach
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 14 days ago
3D and image-based computer vision Experience implementing 3D computer vision algorithms and training end-to-end machine learning models (from data collection and design to evaluation) Knowledge and