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developed mouse models and human tissue processing pipelines. The candidate will learn and use cutting edge immunological methods (high parameter flow cytometry, multiplex imaging, single cell and spatial
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, investigates how smart and autonomous technologies can support social encounters in public space. It brings together Human-Computer Interaction (HCI), Design Research, and artistic research through speculative
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environment and receive training in complementary experimental approaches in cellular and synaptic neuroscience. The project combines primary neuronal cultures, mouse models, advanced fluorescence imaging
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system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing, and machine-learning-based analytics. The research work at NTNU will focus particularly
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Assist in developing AI-based computational tools for analyzing biological images. Help implement machine learning, deep learning, computer vision, and image processing algorithms. Work closely with
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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optimization of machine learning methods for processing Quantum OCT (Q-OCT) signals. Design, training, and testing of neural network architectures for artefact and dispersion removal in Fd-Q-OCT and SS-Q-OCT
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19 Sep 2026 Job Information Organisation/Company Radboud University Research Field Computer science » Modelling tools Computer science » Programming Engineering » Computer engineering Engineering
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physics and building high performance imaging systems. She or he has a demonstrable interest in optics, signal processing, and mathematics or machine learning. The candidate should have an MSc degree in
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Fundacio de Recerca Clinic Barcelona-Institut d'Investigacions Biomediques August Pi i Sunyer | Spain | 7 days ago
or ELISA. Scientific curiosity, eagerness to learn, and strong teamwork skills will be highly valued. Research group: Cellular Immunotherapies for cancer, Sònia Guedan Project: Next-Generation CAR-T Cells