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The Faculty of Engineering, Department Electronics and Informatics, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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students who are prepared for a lifetime of learning and rewarding work. Candidates should hold a PhD or master’s degree in electrical and computer engineering or related fields and should be comfortable
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. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding performance in Physics or related
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., Computational Mathematics, Computer Science, Economics, Finance, Financial Engineering, Information Systems, Machine Learning, Mathematical Finance, Operations Research, Optimization, Probability, And Statistics
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Investigating cyber-physical power system resilience and operation School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline: Applications
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Brain Decoding Models across Subjects School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | 4 days ago
demonstrated the efficacy of employing machine learning approaches to furnish engineers with a rapid computational asset for structural design and monitoring. Given that numerical models incorporating multi
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse