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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 5 days ago
profile # Ph.D. in the field of Physics, Chemistry, Computer Sciences or Applied Mathematics or related field # Background in mathematical surrogate modeling and machine learning # Experience or familiarity
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27 Jan 2026 Job Information Organisation/Company University of Siegen Department Embedded Systems Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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for doctoral programmes: any time Application deadline The annual call usually opens in September. https://www.dashh.org/application/index_eng.html Interim applications are possible under certain conditions
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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to work in. Research groups: Computational Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science
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personal computer and Internet access. Funding opportunities within the university Yes Description of the above-mentioned funding opportunities within the university PhD positions are paid and will cover all
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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning