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Frankfurt School of Finance & Management • | Frankfurt am Main, Hessen | Germany | about 17 hours ago
Combined Master's degree / PhD programme Yes Joint degree / double degree programme Yes Description/content The doctoral programme at Frankfurt School offers rigorous training in Accounting, Economics
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materials with adapted surface properties for electrosorptive CO2 Capturing structural and physicochemical characterization of carbon materials: application of modern analytical methods e.g. XRD, Raman
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PhD programme with a focus on data science and research in the structure of matter. The graduate school covers data challenges from application fields such as structural biology, particle physics
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13 Mar 2026 Job Information Organisation/Company Christian-Albrechts-Universitaet zu Kiel Department Department of Mathematics Research Field Mathematics » Other Researcher Profile First Stage
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and data meet What you contribute Master of Science (or equivalent) in Computer Science, Applied Mathematik, Engineering, Physics, or similar Strong analytical thinking and algorithmic understanding
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 1 month ago
, or quantitative data analysis is advantageous but not strictly required. Our offer A full-time PhD position in a stimulating, international research environment A four-year appointment following successful
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning
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into microscopy image analysis and analytical data analysis workflows, together with other team members Build new foundation models for microscopy image analysis Implement AI-based microscopy image analysis
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining