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Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability
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type, developmental stage, treatment) to build tissue- and context-specific co-regulation networks Design and implement clustering and integration approaches (e.g., network-based and subspace clustering
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data from relevant sources, and build a joint knowledge and data repository. Design effective material counterfactuals: Design, implement, and investigate counterfactual reasoning useful for proposing
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at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender
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Infrastructure? No Offer Description Work group: IBG-3 - Agrosphäre Area of research: PHD Thesis Job description: Your Job: The PhD position is offered in the context of the HDS-LEE graduate school. We are looking
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This KTP aims to position Jesmonite as a market leader in sustainable composite materials. The project's vision is to embed environmental responsibility at the core of Jesmonite's product innovation
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leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/ . Applications are now invited for
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to develop learning-based surrogate
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Infrastructure? No Offer Description Work group: IBG-4 - Bioinformatik Area of research: PHD Thesis Job description: Your Job: Develop methods and workflows to construct robust co-regulation networks from large