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Field
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performance. The project will leverage one-of-a-kind in-process imaging data to gain unparalleled insights into the laminate microstructure. The outcome of this work will be a predictive capability to quantify
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Engineering at Southampton you will benefit from the extensive network of collaborations with members of the group. There will be an opportunity to guide PhD and Master students. Funding is available initially
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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning
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imaging system for immunology. A novel, rapid AAV-mediated technology for generating transgenic mouse models. Comprehensive core facilities for advanced flow cytometry, genomics, and single-cell sequencing
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organoids and co-culture systems. Key Responsibilities & Activities Process patient biopsies/PBMCs, generate single-cell datasets (scRNA/CITE-seq), and identify testable pathways. Validate targets in tissue
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engineering, computer science, physics or related fields). A PhD* (or equivalent research experience) in a relevant subject (only for Research Fellow position). Candidates with a non-healthcare degree are
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Engineering, Biomedical Engineering (Medical Informatics), or related areas. Recipient category: Masters, enrolled in the course: Degree courses: enrolled in doctorate. Non-conferring degrees courses: enrolled
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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Job Description Position Details School of Chemical Engineering Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,636 to £46,049
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 2 months ago
multidisciplinary team involving image processing labs (e.g., CMAP) and French hospitals (e.g., CHU Kremlin-Bicêtre, Hôpital Foch, Institut Mutualiste Montsouris, Institut Gustave Roussy). Phase 1: Design and develop