34 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" Postgraduate positions in Germany
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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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Do students receive financial aid? All doctoral positions are fully funded, including social benefits. Students also receive funding to attend conferences and other events related to their research, and have access to outstanding facilities. Do I need to know English? Yes, English is the...
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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(including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A qualification that is highly valued in industry 30 days of annual leave and flexible working
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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to apply E-mail personal@ufz.de Website https://recruitingapp-5128.de.umantis.com/Vacancies/3332/Description/2 Requirements Additional Information Website for additional job details https://recruitingapp
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow