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collaboration with Q.ANT GmbH in Stuttgart, a deep-tech company that develops photonic computing and photonic sensing products. The goal of this project is the development of highly integrated vapor cells with
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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well as to leading HPS and STS centers in Germany and around the world. The researcher taking on this position will be required to teach 5 hours per week, in accordance with postdoctoral workloads across Germany. The
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. Focus on building deep, strategic, long-term relationships with internal & external stakeholder to be viewed as a partner rather than transactional. Be a “partner in the trenches”—be responsive, engage
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proliferation. The successful candidate should have prior experience in handling genomics, transcriptomics, and single-cell omics datasets. Candidates with sufficient experience in machine learning and deep
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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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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
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science, and applied plant research Example reading: Peleke, F. F., Zumkeller, S. M., Gültas, M., Schmitt, A., & Szymański, J. (2024). Deep learning the cis-regulatory code for gene expression in selected
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and development to improve clinical processes for the benefit of our clinical partners and, in the end, patients. What you will do It has been observed that deep learning models are able to identify