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Dortmund, we invite applications for the Research Group Analysis of Microscopic BIOMedical Images (AMBIOM): PhD Candidate (m/f/d) The position is part of the DFG-funded project: ComplexEye - a 96/384-well
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… Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Your profile PhD degree in physics or similar natural science discipline, signal/image processing, or engineering Interest
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membrane separation processes. Good knowledge of English, and mandatory written and oral proficiency in Portuguese. Selection process Read the job offer at http://www.cebal.pt/images/docs/Posicoes/2026
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-laboratory.com/ Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID): https://www.cuimc.columbia.edu/news/new-columbia-center-will-leverage-ai-enhance-patient-care Department
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Send your CV along with a motivation letter to chloe.lehoucq@pasteur.fr with benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Neuroscience or Cognitive science and the
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of PhD certificate or diploma; Detailed Curriculum Vitae; Motivation Letter. The submission of applications is digital, in pdf format, from 02/03/2026 to 15/03/2026, in the following link: https
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Institut Lumière Matière ILM- UMR 5306 CNRS / Université Claude Bernard Lyon 1 | Villeurbanne, Rhone Alpes | France | about 1 hour ago
properties at different stages of the aggregation process. Funding category: Autre financement public ANR ALICE PHD title: Physique PHD Country: France Where to apply Website https://www.abg.asso.fr/fr
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. Experience with control and synchronization of high-speed imaging and lighting systems. Experience with image post-processing and data extraction. Personal characteristics To complete a doctoral degree (PhD
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https://www.uni.lu/snt-en/research-groups/trux/ . The successful candidate will: Conduct cutting-edge research in multimodal and multilingual natural language processing Develop and curate multimodal
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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