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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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fit to this project; An academic transcript of BSc, MSc and PhD education, including grades; Full Curriculum Vitae, contact information for at least two academic references, and if applicable, a list of
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. The candidates are expected to work in a highly collaborative environment with other lab members and industry collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer
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including high-impact scientific publishing, and collaborative research with international teams. Who we are looking for Requirements MSc degree in Computer Science, Data Science, Machine Learning, or a
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Helmholtz Association of German Research Centres | Oldenburg Oldenburg, Niedersachsen | Germany | 3 months ago
of these areas, a willingness to expand into the others, as well as a general interest in sustainability. They will be proficient in quantitative methods such as causal inference, machine learning, and simulation
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Helmholtz Association of German Research Centres | Oldenburg Oldenburg, Niedersachsen | Germany | 3 months ago
research. The project will combine established methods from historical research with modern approaches from machine learning and network science. Your TasksThe work will involve the analysis of historical
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skills, especially in quantitative and/or mixed methods. Experience with statistical analysis including cluster analysis Comprehensive computer skills, with the ability to learn and utilize new and
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field Computer Skills General office suite and willingness to learn lab specific programs Strong programming skills in R and/or Python Experience with Next Generation sequencing Record of peer-reviewed
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: biomimicry, biofabrication techniques, biomaterials, biosensors, wearable electronics, and machine learning • Experience with mechanical and rheological testing of biodegradable or soft materials • Hands