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multidisciplinary field, and openness to learning new things. The PhD candidate needs to be proficient in spoken and written English and has a Master’s degree. We are offering a modern research environment and
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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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with other 2D and 3D techniques such as H&E and LSFM. The work will be done in close cooperation and synergy with an already running PhD project. Partly existing database will be used and extended
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HF, including chelating ligands, reactive nanoparticles and additives Optimize melt-spinning, uniaxial stretching, and post-treatment steps to control sheath porosity and ion diffusion Acquisition
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datasets with multi-omics profiles of tumors from previous studies Developing new machine learning models through collaboration with the Swiss Data Science Centre Establishing data analysis pipelines