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                with your CAPeX colleagues, you will develop, engineer, and test new experimental approaches which push the state-of-the-art fast and sensitive product detection in electrochemical and electrocatalytic 
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                pharmacology. The PhD project will focus on testing and optimizing antisense oligonucleotides in preclinical in vitro models, as well as formulating these molecules into a novel biodegradable delivery system 
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                Constructing earth-based structures and testing their mechanical and acoustic performance A successful candidate will have a solid background in one or more of the following areas: Machine development and 
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                methods such as NMR, DSC, rheology, or mechanical testing applied to soft polymeric or biomedical materials. Educational background: MSc degree in chemistry, chemical engineering, or materials science, with 
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                formulation, characterization, and performance testing of packaging systems in food applications. This PhD project aims to develop, characterize, and validate bio-based food packaging materials derived from 
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                emergency managers, robotics developers, and public authorities. Is tested and refined in close collaboration with stakeholders through simulation exercises, workshops, and field studies. The project builds a 
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                Analytics. The core focus of the PhD project will be to develop and test planning and optimization models to analyze new and innovative Hospital-at-Home systems to improve access to healthcare for elderly and 
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                test digital prototypes with stakeholders Apply metagenomic sequencing to validate microbial contamination trends Analyze microbiome and operational data to identify risk factors Contribute to teaching 
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                processes You are eager to elaborate on the newest research results, improve ideas, and test/validate by engagement with national and international collaborators A successful candidate will have solid 
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                that can then be tested quickly in the lab rather than remain computational predictions? Do you also wish to work closely with experimental biologists and gain a solid grasp of how experimental work is