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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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27 Jan 2026 Job Information Organisation/Company University of Siegen Department Embedded Systems Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher
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sciences You are organized, reliable, and proactive You are a good communicator and enjoy teamwork You are comfortable working in English ((at least B2 level according to the CEFR: https://go.fzj.de
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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experience with PyTorch. Ideally, knowledge in computer vision and object detection/segmentation. Motivation to independently delve into new and current research topics. Willingness to work with erotic
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 9 days ago
transduce these signals into biological responses. Where to apply Website https://www.hbigs.uni-heidelberg.de/en/your-application Requirements Research FieldBiological sciences » BiologyEducation LevelMaster
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institution. The Cluster of Excellence REC² offers (subject to the availability of resources) at the Faculty of Electrical and Computer Engineering, Institute of Semiconductors and Microsystem (IHM), Chair
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strengths of the University of Tübingen in Computer Sciences and Machine Learning. Potential research directions include, but are not limited to, phylogenetic, demographic, ecological and biogeographic
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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning