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Field
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in September 2026. Physical learning is an emerging paradigm in which materials adapt their behavior through local physical rules, without digital computation. Despite rapid experimental progress, it
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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers
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on diversity and inclusion . How to apply Applications (including a cover letter, CV, most representative academic publications (up to 3), and any additional supporting documentation such as link to code/other
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for functional reactor or fluidic systems. Experience with high-speed imaging, pressure measurements, or cavitation evaluation. Demonstrated ability to work independently while maintaining strong collaborative
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 19 days ago
measurements. Implement physics-informed machine learning models to predict mechanical properties from cell morphology. Collaborate closely with experimental teams to integrate transcriptomic and imaging data
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instrumentation, as well as in the field of Biomedical Imaging applications. The laboratory has developed many interactions with research teams specialized in the fields of oncology, cardiology, tissue engineering
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. This project seeks to overcome key workflow and precision limitations in HDR brachytherapy by enabling real-time adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU
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for the numerical simulation of high-frequency acoustic and electromagnetic waves is a longstanding open problem in computational mathematics. These waves underpin a plethora of communication and imaging technologies
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Previous Job Job Title Post-Doctoral Associate - SME Next Job Apply for Job Job ID 372823 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546
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Previous Job Job Title Post-Doctoral Associate - Quantitative Imaging & Human Retroviruses Next Job Apply for Job Job ID 371962 Location Twin Cities Job Family Academic Full/Part Time Full-Time