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/epifluorescence imaging, and basic image analysis. The role involves tissue processing and data collection across multiple projects, collaborating closely with students, postdocs, and senior lab members. Strong
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operation of the whole lab and participate in on-going project(s) with postdocs and graduate students. Essential Job Duties Assisting postdocs and PhD students with cell culture experiments, data & image
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Postdoc Positions Application Deadline 30 Apr 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2026 Is the job funded through the EU
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Chemical Biological Centre (https://www.umu.se/en/kbc ) at Umeå University and is affiliated with the national Centre of Excellence – Umeå Centre for Microbial Research (UCMR) (https://www.umu.se/en/ucmr
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 18 days ago
AI-assisted research processes across computational biology. Prototype, benchmark, and iteratively improve agentic systems with a strong focus on robustness, transparency, and reproducibility. Conduct
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group and in very close collaboration with Toyota Core AI team. It is further embedded in VISLab , with more than 30 PhD students and postdocs working on theoretical and applied computer vision, deep
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all aspects of the MRI imaging functions, and providing scientific training to MRI users regarding data acquisition, processing and analysis. Support staff, including an experienced technical director
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221 of the Labor Code). We process the remaining personal data you provided us with in your application documents (including your PESEL number, image, or other additional data, if you chose to provide
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural