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Field
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for studies of superheavy elements Produce radioisotopes of the lighter homologs of superheavy elements using PSI's large-scale research infrastructure to test and optimize your ideas Perform innovative
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-responsive polymeric particles and emulsions stabilized by them. Establishment and further development of advanced measurement techniques based on atomic force microscopy. Development and optimization
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carrying out and optimizing research methods, writing SOPs, and passing on know-how to the research group; and Mentors students and/or postdoctoral researchers on research projects, including meeting one
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our website: https://www.list.lu/ How will you contribute? You will join the recently awarded PEARL project FUNG-FACTORY in a team of approximately 10 people – led by Ronald de Vries, dedicated
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PhD in organic chemistry (M/F) – Development of self-optimizing flow reactors for chemical reactions
by Prof. F.-X. Felpin aims to develop a fully integrated flow platform designed to autonomously work from reaction discovery to optimization for scaling up through the massive use of digital
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materials. Integration of developed materials into soft and deformable thermal energy-harvesting devices. Characterization and optimization of the electrical, electrochemical, mechanical, and energy
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical knowledge
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) that connects different countries with the overarching aim to develop cutting-edge human in vitro and in silico biomedical tools to better understand the biology of brain disease/disorders (see: https://visi
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applications for a three-year PhD Stipend from October 1st or soon hereafter in dynamic modelling, simulation and optimization of Power-to-X processes for renewable fuel production. The project is primarily
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representations of physical assets and processes—are emerging as a key technology for improving operational efficiency, reducing downtime, and optimizing energy consumption in smart factories. This PhD project aims