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to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis according to the Danish 7-point grading scale (https://ufm.dk/en/education/the-danish-education-system
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) have received the grade of 10 (or equivalent) for the master's thesis according to the Danish 7-point grading scale (https://ufm.dk/en/education/the-danish-education-system/grading-system ) have a
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 days ago
Signaling (headed by Dr. Natalie Krahmer) at the Institute for Diabetes and Obesity (IDO) develops and applies organelle-resolved proteomic workflows to investigate the cellular processes underlying
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application! We are now looking for 1–2 PhD students for the Division of Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Within the research unit
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Python. You will work in a newly formed team of two postdocs and a PhD student, led by the PI (Ekaterina Ilin), and collaborate closely with both postdocs, who will be working primarily on a large optical
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Science (Information and Signal Processing), Speech, and Cognition. The unit conducts its research through 11 teams organized into 4 research departments: - Automation and System Safety - Data Science
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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postdocs in the SteeleLab in the Quantum Nanoscience Department in Delft. You will meet regularly with your supervisors and other team members, and also be encouraged to develop and explore your own ideas
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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological