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/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 packages
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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for climate-positive and CO2-negative processes. What you will do Optimization of the pilot plant for the combustion of solid fuels (biomass, waste) with oxygen and subsequent CO2 capture Development of models
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industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods
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processes that produce energy and raw materials. The Institute of Radiopharmaceutical Cancer Research develops radiotracers for imaging of cancer biomarkers and personalized therapies. In a joint effort of
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procedure Icon Applicants Applicants Icon Foundation Foundation Icon Notification Notification Nomination Examinationapprox. 1-2 months Review Processapprox. 3-4 months Conferral Nomination documents
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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and/or atom probe tomography Experience in image processing Experience in programming with Python or Matlab is strongly desired Team spirit as well as excellent communication and organizational skills
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/intercultural communication Experience in processing imaging data is a plus Experience with the named imaging modalities or other optical technologies for plant phenotyping is a plus Equal opportunities and