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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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quantum sensors, leveraging state-of-the-art electron microscopy facilities at the Condensed Matter Physics and Materials Science Department (CMPMS) and the Center for Functional Nanomaterials (CFN
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, Electronics, Applied physics, Chemicalphysics or equivalent and fulfil the requirements to be admitted into the XXX PhD program at the Universitat de Barcelona. https://www.ub.edu/escoladoctorat/en/access-and
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Salary. Minimum Requirements: Applicants with a recently awarded Ph.D. degree in a relevant scientific discipline. Preferred Qualifications: Experience in cryogenic electron microscopy (cryoEM) Any
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scattering (SAXS) tensor tomography Develop correlative multi-scale analysis pipelines integrating SAXS tensor tomography and high-resolution X-ray tomography, and complementary electron microscopy data (in
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. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
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Referensnummer IFM-2026-00053 Work assignments This PhD position focuses on methodological and computational development in cryo-electron microscopy (cryo-EM), with emphasis on image reconstruction
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will be characterized using structural techniques (XRD, BET), electron microscopy (TEM, SEM), UV-Vis absorption spectroscopy, and photo- and radio-luminescence. This thesis will be conducted in close
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via operando liquid-phase transmission electron microscopy (LP-TEM). Your tasks: Self-motivated and independent planning, execution, and analysis of research in the scope of operando electrocatalysis
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lively community of PhDs and Postdocs within its members, see https://www.arts.kuleuven.be/english/research/becoming-researcher . The Archaeology Research Unit joins the Research Units of Arts Sciences and