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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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sytnhesis and functionalization, materials science, characetrization techniques and in vitro/in vivo prototype validation in relevant environments. The candidate will work as part of an international team and
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. MAIAMI aims to establish a paradigm shift in materials science by embedding mechanistic AI agents into physical experimentation cycles—enabling rapid, transparent, and reproducible design of advanced
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 1 month ago
techniques and imaging technologies, the unit delivers cutting-edge solutions with real-world impact. Led by Prof. María Cuartero (ERC Fellow) and Prof. Gaston Crespo, UCAM-SENS fosters innovation, education
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(direct and indirect pathway neurons) in mouse models of HD, and to dissect the regulatory role of m6A RNA methylation in these processes. The project will combine in vivo and in vitro approaches, advanced
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environment Excellent communication skills Desired: Experience and knowledge of histological laboratory techniques Experience with specialised software for image and data analysis Scientific Contributions
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tumor-on-a-chip models fabrication and set-up Experience in confocal microscopy and imaging Excellent organizational and multitasking abilities Strong time-management skills Advantageous: Knowledge in
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markers, control Marfan and OKD48 mouse colonies; surgery for extraction of various organs. The candidate will join the lab of Gustavo Egea (Vascular Cell Biology Lab), which is currently comprised of 1
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applications will be probed in order to validate the implementation of these techniques in key computer vision-related tasks, such as image classification, multimodal data generation, or manipulation of graph
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transistors to solve some of society’s most pressing computational challenges. Silicon-based approaches to quantum information processing offer advantages for scaling such as high qubit density, record qubit