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defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
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://www.uni-muenster.de/Geoinformatics/en/Studies/study_programs/PhD/application/index.html Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree
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Europe. In the Monitoring & AI department, you will be involved in the development and implementation of AI and machine learning (ML) tools for monitoring and operation of CO2 storage sites. Key
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 20 hours ago
The PhD programme is open to national and international students who hold a Master's degree or equivalent in Environmental Science, Environmental Engineering, Environmental Economics, Environmental
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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CMFI Cluster of Excellence iFIT Cluster of Excellence Machine Learning CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC-TRRs
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Profile Areas Cluster of Excellence CMFI Cluster of Excellence iFIT Cluster of Excellence Machine Learning CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 2 days ago
the IMPRS CoNI is English, German language skills are not mandatory. For PhD applicants, a minimum score required for a TOEFL paper-based test is 550. The minimum score for the TOEFL computer-based test is
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at conferences. The PhD program has a duration of three years and with the PhD degree offered by TUM. Qualifications A Master’s degree in Operations Management, Computer Science, Industrial Engineering, Economics
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault