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nanomedicine concepts to design and formulate lipid-based nanoparticles for the controlled co-encapsulation and delivery of multiple nucleic acid cargos. Quantitatively characterize nanoparticle structure, cargo
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dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning. The ideal candidate has
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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experience to establish themselves as future group leaders at Empa. This is part of our broader commitment outlined in our Diversity Action Plan and relates to specific goals that are regularly implemented
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(acoustics/multi-physics simulation, experimental planning, setup, measurements, analysis) Conceptualization and realization of novel setups (hardware integration, CAD design, assembly, etc.) Software
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. Empa is a research institution of the ETH Domain. Empa’s Laboratory Materials for Energy Conversion focuses on materials and device innovation for sustainable energy conversion and storage technologies
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. Empa is a research institution of the ETH Domain. Empa’s Laboratory Materials for Energy Conversion focuses on materials and device innovation for sustainable energy technologies. Your tasks The aim
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work will involve: Design and synthesis of injectable hydrogel systems Encapsulation and controlled delivery of probiotics and bacteriophages Engineering and characterization of phage-based antimicrobial
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of scientific articles in peer-reviewed journals Presentation of research results at international conferences and scientific meetings Your profile PhD in Physics, Materials Science, Electrical Engineering
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degree in Physics/Photonics/Engineering or equivalent Experience: Laser applications (measuring, processing, etc.), optical system design, assembly and usage Skills: Hands-on experimental mindset, strong