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- International Iberian Nanotechnology Laboratory (INL)
- University of Newcastle
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published on EURAXESS in April 2025, with the respective application period defined therein. This republication aims solely to correct the information regarding the funding source of the project SMART-CRM
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to the republication of the Call Digitalisation/BI2, originally published on EURAXESS in August 2025, with the respective application period defined therein. This republication aims solely to correct the fellowship type
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Free State of Bavaria) in Germany, in part using case studies to test and assess the new approach. You will work primarily on one of these case studies, a medical device prototype, by formalising
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to successfully deliver a prototype for the detection and identification of bacteria through the effective monitoring of their associated Volatile Organic Compounds emission. Job Duties The job duties will be
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photographic documentation. Production of derived visual content: Generation of renders, animations, and illustrative images from 3D models for reports, scientific publications, and digital communication, with
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of micropollutants; (iii) characterizing and quantifying biomass using microscopy and quantitative image analysis techniques; (iv) relating the obtained data through the application of multivariate statistics
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 6 days ago
of the following R&D activities: - Manipulation and testing of animal models using photometry techniques or miniature microscope imaging to monitor calcium or neurotransmitter signals; - Analysis and interpretation
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Instituto de Investigación Sanitaria Puerta de Hierro – Segovia de Arana (IDIPHISA) | Spain | about 1 month ago
Imaging with the category of Senior Specialist in Professional Group II for the functional area 2 scientific-technical. (MECES 3. EQF7). The Cardiology research area is made up of six researchers and is
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#nanotechnology #advanceddevices Overview The Alpuim Research Group focuses on CVD growth, transfer, and device fabrication, using 2D materials, clean-room technology, and Raman imaging for structural
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images or text Using techniques such as Linear Regression, Random Forest, and Classification Experience with Machine Learning approaches such as applications of Convolutional Neural Networks Applications