22 bayesian-object-detection Postdoctoral positions at Technical University of Munich in Germany
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strong academic background in robotics and a keen interest in advancing the frontiers of deformable object manipulation. Ideal candidates are those aiming for a long-term research career in academia
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the collection and processing of personal data as part of your application. By submitting your application, you confirm that you have taken note of TUM's data protection information. Find out more about us at
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skills as well as very good English skills. Preferred Qualifications: • Strong interest in RISC-V, architecture and High Performance Computing • Experience with low level software and tools Key objectives
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objective of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins as well as relevant mechanisms, which allow optimizing
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provided by TUM. Find out more about us at www.tum.de. We are not accepting applications for this job through MathJobs.Org right now. Please see the job description above on how to apply. Contact: Professor
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of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/ . By submitting your application, you confirm to have read and understood the data protection information provided by TUM. Find out
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number: 20250415_092016 Privacy Notice: As part of your application for a position at the Technical University of Munich (TUM), you are providing personal data. Please take note of our privacy information
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protection information provided by TUM. Find out more about us at www.tum.de. We are not accepting applications for this job through MathJobs.Org right now. Please see the job description above on how to apply
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detection, segmentation, and quantification of diseases such as cancer, the generation of novel representations of pathology data for further processing, or the discovery of virtual biomarkers for patients
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premature deaths, especially among children, people with certain medical conditions and the elderly. With roughly 91% of the population living in urban areas and breathing polluted air, miniaturized detection