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Job Id: 11135 Fixed-term of 3 years | Part-time with 65% (25 hours/week) | Salary according to TV-L E13 | Clinic for Radiology / Experimental Magnetic Resonance Group We are UKM. We have a clear
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questions in the areas of self-supervised/label-efficient learning and explainability of deep neural networks (XAI) are being developed, particularly for use in biomedical applications. Further information
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Reference Number: 11180 Fixed-term of 3 years | Part-time with 65% (25 hours/week) | Salary according to TV-L EG13 | European Institute for Molecular Imaging We are UKM. We have a clear social
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2025. The FZE develops methods for the precision analysis of cells based on principles and techniques from analytical chemistry, biotechnology and biophysics. What you will do The Master's thesis is part
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approaches are gaining importance for autonomous vehicles. However, the training and certification of autonomous systems with machine learning components is a huge challenge, since the learned behavior is
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context, we developed label-free NAD(P)H fluorescence lifetime imaging (FLIM). We previously found (i) that during the life cycle of helminths, i.e., H. bakeri in mice, both bioenergetic and defense
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to fill the position of a Researcher (m/f/d) – Text Mining for Biodiversity Knowledge (Entomology and Legacy Texts) full-time / part time Location: Müncheberg (Brandenburg) Employment scope: full-time
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the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires
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the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires
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of neurons to become active during spatial navigation, in mice. To this aim, the candidate will investigate longitudinally - by using head-fixed two-photon imaging in combination with cellular labelling