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these challenges by advancing machine learning (ML)-based and data-intensive methods for the scalable design, processing, and deployment of DPPs. The advertised PhD position focuses on developing ML-based and
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English English PhD Research Fellow in Machine Learning and Distributed Data Processing Apply for this job See advertisement Job description Position as PhD Research Fellow in Machine Learning and
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, geometric deep learning. Considered an advantage: experience in programming or course work in computer science, algebra, topology or differential geometry, knowledge of topological data analysis or machine
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or course work in computer science, algebra, topology or differential geometry, knowledge of topological data analysis or machine learning will also be a benefit. Qualifications and personal qualities
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, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students in
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are expected to submit a career development plan, specifying career goals and the competencies that the PhD fellow should acquire, no later than one month after commencement of the fellowship period. The
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analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with staff and our current PhD students. PhD research fellows receive
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master’s degree have until 1st of July 2025 to complete the final exam. Desired qualifications: Experience in areas such as machine learning, computer vision, control sys-tems, perception, control
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engineering (elkraft). Experience in cybersecurity incident management. Experience in machine learning/artificial intelligence methods. Experience in simulation and modeling. Applicants will be assessed
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models