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to machine learning is well funded and continuously publishes in high impact journals. We foster a creative working environment, where you will find freedom to implement, develop, and publish research
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engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 5 Feb 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not
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. PhD Project Description Project Title: Photonic-Inspired Federated Learning for Communication-Efficient Next Generation Radio Access Networks (NG-RANs) Description: This PhD project will develop a novel
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-cell genomics data, ideally using tools such as Seurat or Scanpy Enthusiasm for statistical modeling and machine learning to analyze complex biological datasets High level of care and attention to detail
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) and Machine Learning/NLP (Natural Language Processing) to capture both the network embeddedness and the qualitative B2B relationship features of supply chains. The project identifies key bottlenecks
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have activity in quantum optics, so
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conferences and workshops. The Research Assistant Professor may be asked to teach (or may ask to teach) but that is neither required nor guaranteed. Qualifications Applicants must have a Ph.D. in Economics or
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | about 9 hours ago
you will learn the specific methods you need for your project Feedback from experienced research advisers Excellent research facilities Instruction in English Thesis may be written in English or German
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and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed