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the first call lasts from the 1st of July to 31st of August 2025. Description of specific PhD projects: Machine Learning Interatomic Potentials for Chemical Reactions Hosting: Tallinn University of Technology
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Europe | about 18 hours ago
manufacturing, development of machine learning algorithms and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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, and therapy resistance mechanisms Ability to work independently and collaboratively within interdisciplinary teams Prior experience with network modeling or machine learning is a plus We offer
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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: TRR408-A7 Investigators: Prof. Dr. Ostap Okhrin, Chair of Econometrics and Statistics esp. in the Transport Sector and co-supervised by Prof. Dr. Kai Nagel, Chair of Transportation System