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of Excellence boasting world-class facilities and advanced nanofabrication capabilities. WHEN? Planned start date: Late 2025 / Early 2026 REQUIREMENTS: (1) Master's degree in Physics, Nanotechnology, Materials
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Predoctoral researcher at the Targeted Therapeutics & Nanodevices Research Group (Project BRAINZYME)
physiological conditions. • Examine their performance in 2D and 3D systems, including chemical and genetic disease models, multi-cultures and organ-on-a-chip devices. • Investigate the biodistribution as
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(quantitative and qualitative) to monitor gene expression, neuronal activity, and metabolic changes during disease modeling and therapeutic testing. This PhD project offers the opportunity to work in a
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, in a creative and stimulating scientific environment. Opportunities for short stays in distinguished international research institutions. Opportunities for complementary training in both technical and
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scalable and efficient software and firmware analysis methodologies using tools like Frida or IDA Pro, enhanced with traffic monitoring techniques and Machine Learning to detect and analyze vulnerabilities
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IBE. We are a small, but collaborative and dynamic group. The candidate will benefit from a vibrant and interdisciplinary academic environment with excellent opportunities for education, training, and
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from dual supervision, including co-direction by Dr. Kalanit Grill-Spector (Stanford University), with the opportunity for a short-term research stay at Stanford. International conference travel and
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Ràpita (Tarragona), with short stays at IRTA Torre Marimon (Caldes de Montbuí, Barcelona) as needed to carry out microbial ecology analyses and laboratory-scale experiments. Field measurements of soil and
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, Barcelona) centre for the first 18 months to conduct microcosm experiments and will then continue the research period at IRTA la Ràpita (Tarragona). Throughout the predoctoral stage, short research stays
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or equivalent Skills/Qualifications Valued/Preferred qualifications: Experience in software solution development Experience with machine learning models Experience in R&D&I projects (Research, Development and