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Field
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applications using patient-specific data Very strong expertise in the theory and application of Physics Informed Neural Networks to inverse problems Expertise in sensitivity analysis and uncertainty
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letter with your application. Describe a deep learning project you have executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational
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executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational structural biology projects are especially relevant. Discuss results, limitations
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15 Apr 2026 Job Information Organisation/Company ENSEMBLE3 Sp. z o. o. Research Field Physics Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Application Deadline 28 Apr
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Application form should be filled and all required documents uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz Website for additional job details https://www.fd.cvut.cz/en
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for field visits to be carried out. Additional Information Website for additional job details https://www.univ-smb.fr/wp-content/uploads/2026/04/offreemploi-postdoc_2026_lis… Work Location(s) Number of offers
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Job Description Job Alerts Link Apply now Research Associate (Comparative Effectiveness and Real-World Data Analytics) University-Level Unit: Saw Swee Hock School of Public Health Faculty/Department
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optimization of advanced reconstruction and control algorithms, combining numerical modeling, inverse problem techniques, and AI-driven approaches, together with experimental validation to improve imaging
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to antennas and antenna arrays, and the solution of inverse problems and elec-tromagnetic imaging. Required teaching duties: in the disciplines of the research sector IINF-02/A and within the PhD programs
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Lehrstuhl für Angewandte und Computergestützte Mathematik | Aachen, Nordrhein Westfalen | Germany | 6 days ago
Dissipative Dynamics, the international research training group Modern Inverse Problems, the SNuBIC research unit, the Sparsity and Singular Structures collaborative research center, as well as with the School