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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 3 days ago
. PhD students will be funded for three years with possibility of extension and have to enroll in a PhD program at the Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences (GGNB
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integrated into the International PhD Programme (IPP; https://www.imb.de/phd ), which is organized by IMB ( www.imb.de ). The IPP offers an exciting, interdisciplinary and lively international community
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Application deadline Applications must be received by 15 August. Tuition fees per semester in EUR Varied Combined Master's degree / PhD programme No Joint degree / double degree programme Yes Description
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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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validation, and regulatory reporter assays. Learn more about the group here . YOUR MISSION: Investigate how genetic variants affect male reproductive function Perform single-nucleus and bulk RNA sequencing
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time Application deadline No application deadline Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content The PhD
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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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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-RTG PhD student, you will be integrated into the International PhD Programme (IPP; https://www.imb.de/phd ), which is organized by IMB ( www.imb.de ). The IPP offers an exciting, interdisciplinary
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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven