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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with
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of Econometrics and Statistics, esp. in the Transport Sector and co-supervised by Prof. Dr. Klaus Bogenberger, Chair of Traffic Engineering and Control, TU Munich. Requirements: Excellent, very good or good
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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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research centers. CADIA provides a collaborative environment where researchers tackle challenging problems in AI, machine learning, and human-computer interaction. The center offers regular seminars
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a
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Experience in electroencephalogram and electrospinogram, other biosignals Experience in biosignal processing Experience in nerve stimulation Knowlege in machine learning Very good written and spoken English
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Computer Science and Computer Engineering with specialisation in Information Systems. In the context of Prof. Fridgen's PayPal-FNR PEARL Research Grant and the FutureFinTech National Centre of Excellence in Research