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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 1 day ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position in Machine Learning for Single-Cell Genomics (f
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). The ideal candidate brings a strong machine learning foundation, curiosity about sound and music computing, and enthusiasm for collaborating with PhD students and postdocs. You will help combine individual
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fields. Your research can be theoretical, applied, or span both. Deadline February 9, 2026. Where to apply Website https://jobrxiv.org/job/ellis-institute-finland-27778-postdocs-in-machine-learn
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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork
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experimental approaches, including machine learning, genomic assays, and live imaging of subcellular dynamics coupled to CRIPSR-based genome engineering. Much of the experimental work is carried out in live
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described in our strategic vision, Pro Futuris, and academic strategic plan, Illuminate. Connections working at Baylor University More Jobs from This Employer https://main.hercjobs.org/jobs/22078479/postdoc
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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/16 04:59 AM UnitedKingdomTime (posted 2025/11/04 05:00 AM UnitedKingdomTime, listed until 2026/05/05
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and