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of protein gels, microgels, fat mimetics, and structure–function relationships in food matrices. Familiarity with sensory evaluation, texture analysis, and rheological measurements, food system
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containing a large excess of wild-type DNA. Experience working with urine, clinical samples, wastewater or other complex biological matrices. Knowledge of integrating nucleic-acid amplification with a non
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, experience and personal qualities. All documentation must be provided in a Scandinavian language or English. If the attachments exceed 30 MB in total, they must be compressed before uploading. Please note that
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technologies, such as extrusion, lamination, gelation, or emulsion‑based structuring. Knowledge of protein gels, microgels, fat mimetics, and structure–function relationships in food matrices. Familiarity with
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to determine material properties of reclaimed steel. Investigate geometric imperfections, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data
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Sensing (DAS) data processing and compression using ML Physics-driven machine learning for geophysical modeling and inversion Thus, the candidate is expected to have or about to have a PhD in a relevant
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, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models