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. Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https
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Forschungsinstitut für Nutztierbiologie (FBN) | Dummerstorf, Mecklenburg Vorpommern | Germany | 22 days ago
application or travel expenses in connection with the application. By submitting your application, you consent to the processing of your personal data for the purpose of the application procedure. For more
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
. The group’s work in this area has led to best paper awards at PacificVis and Graph Drawing, with recent publications in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum
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slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is the development of meta-optimization techniques that can automatically search
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using functional 2D materials. • Organic synthesis and typical characterization methods, as NMR, FTIR, MS, EA, UV-vis and fluorescence spectroscopy. • Methods for 2D materials processing and
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longer-term immune responses. Specifically, they play key roles in pathogen recognition, antigen uptake, processing and presentation, but also contribute to tissue homeostasis, tolerance to commensal
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degree in physics, (physical) chemistry, or material science. Knowledge in the operation of ultrahigh vacuum equipment and using X-ray spectroscopies is mandatory. Background in photovoltaic materials
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how oxygen, nutrients, pollutants, or fine sediments migrate between surface water and the bed, or to quantify how restoration actions affect life-sustaining processes such as fish spawning and methane
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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