19 evolution "https:" "https:" "CMU Portugal Program FCT" PhD positions at Empa in Switzerland
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field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision of students Your
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. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-on-antimicrobial-materi… Requirements Research FieldChemistryYears
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Opportunity to work in a network of 15 PhD students in parallel Opportunities to present work at scientific conferences and to publish in high quality journals Personal and professional development support You
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is offering a PhD position focused on development of nanoengineered antimicrobial coatings. This project aims to tackle the growing challenge of infections caused by resistant bacteria through
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to support the development of sustainable, resilient, and
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of ceramic powder and the densification using the cold sintering processing method. The focus of the project is the development ferroelectric lead free ceramics sintered below 500°C and the analysis
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environment with excellent infrastructure for personal and professional development. This PhD project will be carried out at Empa St. Gallen under the supervision of Dr. Paula Navascués. The PhD Student will be
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. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-data-driven
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development of new sensors, support nanoparticle-based cellular reprogramming strategies and identify new omics-based biomarkers. We work closely with clinical partners and we focus on deep understanding
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive