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) workflows for learning from large-scale imaging and molecular data Develop ML models to investigate cellular responses, particularly in cancer cell lines Develop DL models for molecular design based on time
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methods when limited data is available. Large neural networks are known to be heavily inefficient in this limit, and we aim to discover better methods for this purpose. We would like to study how prior
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in a large project rather than on your own in a single project. The following experience will strengthen your application: Experience in energy storage, organic synthesis, or materials characterization
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construction. Information about the research environment The PhD student will join the research environment Architecture, Media, and Material Practice (AMMP) at the Department of Architecture and Civil
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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compatibility with industrial applications. The position is part of a large EU project SurfToGreen where you will have the opportunity to interact with world-class researchers in a multidisciplinary environment