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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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communication skills and ability to network effectively and interact with a diverse range of students and staff. Demonstrated ability to work in a team, collaborate across disciplines and build effective
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knowledge exchange strategy. Contribute to the development and maintenance of the University’s local, national and international academic and community networks related to Centre-related research. Work
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., community, industry players). International work experience or experience in national and international networks, and experience with academia and industry cooperation. Knowledge of existing technical
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research activities. Develops proficiency in career skills, including writing, public speaking, networking, and critical evaluation of scientific literature. Presents scientific work both inside and outside
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through soft, disordered materials, including auto-regulated networks, composite soft solids, and exotic photonic biomaterials. The lab has two fully funded PhD and/or postdoctoral positions available
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access to state-of-the-art facilities and expert assistance with improving your proposal writing skills and feedback on grant applications. We actively facilitate building your professional networks, both
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, and engage with a vibrant network of national and international collaborators. The recruited candidate will work in the AIMLeNS lab lead by Assoc. Prof. Dr. Simon Olsson at Chalmers University
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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, Quebec J1K 2R1, Canada [map ] Subject Areas: Theoretical Physics / Quantum Optics Quantum Information Science Appl Deadline: 2025/09/01 11:59PM (posted 2024/08/29, listed until 2025/09/01) Position