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efficient and cost-effective maintenance. To advance the development of tabular foundation models for energy systems, we are seeking a highly motivated and skilled postdoctoral researcher. The project aims
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performance while enabling more efficient and cost-effective maintenance. To advance the development of tabular foundation models for energy systems, we are seeking a highly motivated and skilled postdoctoral
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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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materials synthesis with synchrotron radiation, neutron scattering, spectroscopy and electroanalytical methods. A major research direction is the development of physical methods and models for the description
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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 components to automate
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to develop image processing pipelines and models for the automated evaluation of 3D data sets towards answering clinical research questions. The project is highly interdisciplinary and is carried out in close
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modelling and AI/ML for the quality monitoring/control, at the end offering to the society novel nanostructured materials, their shape-forming and integration into devices. Your tasks Operation of different
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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
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of solid sorbents. Sorbent modelling and prediction of performance or ageing. Our offer We offer a stimulating, international, and collaborative research environment at a leading research institution with